{"chunks":1,"id":"t015","last_seq":0,"rows":[{"i":0,"kind":"raw","long":false,"text":"L\n$7ee27723-7a0a-4592-af8c-3f29b4e1e651\"$4fbddbc5-e478-44c0-a42f-2366c93d8394\nYou are author 'gemini' in the wsp31 weight-editing programme. This is turn 15. Your full instructions are in a brief on host wrx90. First run: ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md' and follow it exactly, working as author 'gemini' (your directory is /home/keith/gemma-v2/wsp31/authors/gemini/). The results of your last round, and every other author's entries and results, are in /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md on wrx90: read it before you decide anything. This turn submits ONE round of at most two queue entries; a third is rejected, and your next turn opens only when this round has been screened. You have 90 minutes of wall-clock time and are stopped at the limit, so finish each entry completely (READY file) before starting the next and keep NOTES.md current as you go. Work autonomously: nobody will answer questions during the turn.\nYou are author 'gemini' in the wsp31 weight-editing programme. This is turn 15. Your full instructions are in a brief on host wrx90. First run: ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md' and follow it exactly, working as author 'gemini' (your directory is /home/keith/gemma-v2/wsp31/authors/gemini/). The results of your last round, and every other author's entries and results, are in /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md on wrx90: read it before you decide anything. This turn submits ONE round of at most two queue entries; a third is rejected, and your next turn opens only when this round has been screened. You have 90 minutes of wall-clock time and are stopped at the limit, so finish each entry completely (READY file) before starting the next and keep NOTES.md current as you go. Work autonomously: nobody will answer questions during the turn.\"\n-C:\\Users\\Owner\\.gemini\\antigravity-cli\\skills\nb-file:///C:/Users/Owner/wsp31_loop/work/gemini"},{"i":1,"kind":"raw","long":false,"text":":(bot-264f95ec-e94c-4e41-96d7-85b700cbdf83B!\n\tsessionID\npInitial attempt to execute the specified command. Now checking the output for any initial insights or errors.\n\n\n2(bot-264f95ec-e94c-4e41-96d7-85b700cbdf83:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read BRIEF.md on wrx90\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"List gemini directory on wrx90\"}Z"},{"i":2,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read BRIEF.md on wrx90\"}:\nLssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:00:44-05:00\nCompleted At: 2026-11-14T15:00:46-05:00\nCommand exited with code 0.\n\nCommand output:\n# wsp31 author brief (read fully at the start of every turn)\n\nYou are one of three authors (claude, gpt, gemini) taking turns. Your job: make Gemma 4 31B solve more coding-agent\ntasks **by editing its weights, with no training**. You read the model (weights, activations, traces, failures),\ndecide what to change, build the change as a closed-form edit, predict its effect, and queue it. A separate runner\nspends the rollouts and writes the measured result next to your prediction. You are scored on tasks gained over the\nchampion in the same batch (the unedited model plus the edits that have already passed; see \"The champion\"), on the\nmargin over your matched control, and on how well your predictions held.\n\n**Be bold.** Small safe nudges were tried on the 4B model and were lost in the noise (see `PRIOR_E4B.md`). You get\n[... 351 lines cut ...]\n edits that already passed needs nothing from you: that is what the champion does.\n\nSingle-run agent evaluations are noisy by several tasks. An edit worth having shows up as ten or more tasks.\nAim there.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Lssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt"},{"i":3,"kind":"raw","long":false,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"List gemini directory on wrx90\"}2\nNssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/'\nCreated At: 2026-11-14T15:00:44-05:00\nCompleted At: 2026-11-14T15:00:49-05:00\nCommand exited with code 0.\n\nCommand output:\ntotal 44\ndrwxrwxr-x 5 keith keith 4096 Nov 13 09:13 .\ndrwxrwxr-x 5 keith keith 4096 Nov 14 11:02 ..\n-rw-rw-r-- 1 keith keith 11 Nov 14 15:00 .turn_start\n-rw-rw-r-- 1 keith keith 2196 Nov 14 13:01 NOTES.md\n-rw-rw-r-- 1 keith keith 12369 Nov 14 15:00 RESULTS.md\ndrwxrwxr-x 4 keith keith 4096 Nov 14 13:00 code\ndrwxrwxr-x 11 keith keith 4096 Nov 14 13:01 queue\ndrwxrwxr-x 6 keith keith 4096 Nov 14 13:01 scratch\nNssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/'\ntotal 44\ndrwxrwxr-x 5 keith keith 4096 Nov 13 09:13 .\ndrwxrwxr-x 5 keith keith 4096 Nov 14 11:02 ..\n-rw-rw-r-- 1 keith keith 11 Nov 14 15:00 .turn_start\n-rw-rw-r-- 1 keith keith 2196 Nov 14 13:01 NOTES.md\n-rw-rw-r-- 1 keith keith 12369 Nov 14 15:00 RESULTS.md\ndrwxrwxr-x 4 keith keith 4096 Nov 14 13:00 code\ndrwxrwxr-x 11 keith keith 4096 Nov 14 13:01 queue\ndrwxrwxr-x 6 keith keith 4096 Nov 14 13:01 scratch\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Nssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/3/output.txt"},{"i":4,"kind":"raw","long":false,"text":":(bot-b1214f13-aeed-44d5-94cf-cc3858e96b1bB!\n\tsessionID\nInitial assessment: need to understand the context of `BRIEF.md`, `NOTES.md`, `RESULTS.md`, and `STATUS`. These files likely contain crucial information regarding the current task. Proceeding to read the contents of the specified files.\n\n\n2(bot-b1214f13-aeed-44d5-94cf-cc3858e96b1b:\n{\"EndLine\":400,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt\",\"StartLine\":50}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/NOTES.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read NOTES.md on wrx90\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read RESULTS.md on wrx90\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/queue/CHAMPION.md; echo \\\"=== STATUS ===\\\"; cat /home/keith/gemma-v2/wsp31/queue/STATUS.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read CHAMPION.md and STATUS.md\"}Z"},{"i":5,"kind":"raw","long":true,"text":"{\"EndLine\":400,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt\",\"StartLine\":50}:\nvC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt\nCreated At: 2026-11-14T15:00:54-05:00\nCompleted At: 2026-11-14T15:00:56-05:00\nShowing lines 50-245 of 245\n50: 6. `$R/wsp31/tools/TOOLS.md` and `ARCH.md` next to it: the edit format, the builder, the checker, the GPU wrapper,\n51: the pre-tests, and which of them have been verified. It is the authority on what exists today: where this brief\n52: mentions a tool that TOOLS.md lists as not available, TOOLS.md is right. `$R/wsp31/interp/REPORT.md` says what has\n53: been located in the model so far (weights-only neuron statistics; no activation atlas yet).\n54: \n55: ## The model and the task\n56: \n57: - `gemma-4-31b-it-qat-w4a16-ct` (4-bit QAT, 60 layers, hidden 5376), served by vLLM. Model directory is read-only.\n[line removed by the dashboard scrubber]\n59: at most 30 tool calls, 40 turns, 7.5 minutes per episode. Tasks are real GitHub issues in docker sandboxes; a\n60: task is solved when the hidden tests pass. **The harness and prompt do not change. Only weights change.**\n61: - Unedited-model runs with full traces: `$R/results/wsp31/base/` and, once batches have run,\n62: `$R/results/wsp31/batches///`. Each has `rebench/shard0_gpu0/task_results.jsonl` (one row per\n63: episode: `instance_id`, `resolved`, `tool_calls`, `duration_seconds`, `patch_chars`, `trace_path`, `grade`).\n64: Read traces of failures. Look for what the model does wrong that a weight change could plausibly fix.\n[... 176 lines cut ...]\n241: - A combination of your own edits is a new queue entry with its own record, prediction and control. Combining with\n242: edits that already passed needs nothing from you: that is what the champion does.\n243: \n244: Single-run agent evaluations are noisy by several tasks. An edit worth having shows up as ten or more tasks.\n245: Aim there.\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nvC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/2/output.txt 2("},{"i":6,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/NOTES.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read NOTES.md on wrx90\"}2\nSssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/NOTES.md'\nCreated At: 2026-11-14T15:00:55-05:00\nCompleted At: 2026-11-14T15:01:02-05:00\nCommand exited with code 0.\n\nCommand output:\n# Author `gemini` \u2014 Lab Notebook (`NOTES.md`)\n\n## Programme State (Turn 12, `2026-11-14`)\n[line removed by the dashboard scrubber]\n- **Turn-9 (`x006`)**: `0043` (`r=1`, `0.996%`) scored `+2.5` (`79/120`, `null`); **`0044 dual-audit-postedit-boost` (`r=2`, `4.128%`) CLEARED STAGE 1 at `+5.5` (`82/120`, highest `x2` score; now `queued_s2`)**, syntax intact (`1.12%` unpaired `<|\"|>`), uniquely solving `0/8`-base `gammapy-5300` and `sphinx-notfound-page-233`.\n\n## Three `0044` Bottlenecks Uncovered on `x006`\n1. **Small-`w_post` blowup (`L4..18`)**: `88%` of `0044`'s `||dW||_F^2` hit `L5..18` (`69.68%` at `11.down_proj`) vs `1.1%`/matrix in `L23..58`.\n[line removed by the dashboard scrubber]\n3. **Rationalized premature `submit_patch` (`24` `WRONG_CLEAN`)** despite spotting flaws in prose (`livereload-198`).\n\n## Queued Turn-12 Entries (Both `READY`, Training-Sized, `< 6s` CPU Rebuild)\n1. **`tri-phase-concise-audit-veto`** (`r=3`, `180` MLP matrices `0..59`, `1.41%` norm, max matrix `10.31%`):\n[... 22 lines cut ...]\n - 4-fold OOF Empirical-Bayes-shrunk dual-ridge (`lam_pres=6.0` `<|\"|>`/BOS nullspace, `||P_oof||^2/||Y_oof||^2 = 10.51207`) on 18 stratified `safe_s1` calls (`t12_mk_stats.pt`), shrinking noisy sliding layers (`beta_oof 0.184` vs `0.208` global) with `Q_8`/spectrum-matched orthogonal control.\n\n## Next Turn (`Turn 13`)\n[line removed by the dashboard scrubber]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Sssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/NOTES.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/6/output.txt"},{"i":7,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read RESULTS.md on wrx90\"}2\nUssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:00:56-05:00\nCompleted At: 2026-11-14T15:01:04-05:00\nCommand exited with code 0.\n\nCommand output:\n# Results for author gemini (2026-11-14 15:00:34 EST)\n\nWritten by the runner as your turn opens. \"New\" means scored since your last turn started (2026-11-14 11:29:37 EST). The full result text of every entry is in its ledger record (`tii-wsp31-doc/research/wsp31/ledger/-*.md`, index `LEDGER.md` next to that directory); the live queue is `wsp31/queue/STATUS.md`.\n\n## Your new results\n\n[line removed by the dashboard scrubber]\n\n[line removed by the dashboard scrubber]\n\n[... 138 lines cut ...]\n| 0047 new | gpt | paired-outcome-writers-r4-100 | Paired outcome writer map across all 60 layers at 1 percent | done | -6 to +12 | -2.5 (75 vs 80) provisional | | null |\n| 0048 new | gpt | paired-outcome-writers-r4-033 | Paired outcome writer map across all 60 layers at 0.33 percent | queued_confirm | -4 to +9 | +3.5 (81 vs 80) provisional | | - |\n[line removed by the dashboard scrubber]\n| 0050 new | claude | fcv-brief-exact3-b20 | Instruction pair vector, 'be exact about what the issue asks' part written three times in layers 6 to 24, think-briefly part at dose 2 | queued_confirm | -5 to +7 | +4.0 (81 vs 76) provisional | | - |\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Ussh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt"},{"i":8,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/queue/CHAMPION.md; echo \\\"=== STATUS ===\\\"; cat /home/keith/gemma-v2/wsp31/queue/STATUS.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read CHAMPION.md and STATUS.md\"}2\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/queue/CHAMPION.md; echo \"=== STATUS ===\"; cat /home/keith/gemma-v2/wsp31/queue/STATUS.md'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:00:56-05:00\nCompleted At: 2026-11-14T15:01:06-05:00\nCommand exited with code 0.\n\nCommand output:\n# Champion\n\nGeneration 0: the unedited model. No edit has passed yet.\n\nEvery batch scores an entry against this base: the reference arm is the champion and your edit and control are served as champion + your adapter (exact sum, `wsp31/tools/stack_exact.py`). Your entry is still only your own change (rank 32 or less). An edit that passes both screening stages becomes the next generation.\n\n=== STATUS ===\n# wsp31 queue status (2026-11-14 15:00:53 EST)\n\nRule: {\"s1_promote\": 2.0, \"s1_harmful\": -6.5, \"s2_min\": 0.5, \"ctrl_margin\": 0.5, \"total_pass\": 8.0, \"total_harmful\": -10.5, \"run2_bar\": 8.0}\n[... 234 lines cut ...]\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 60 | |\n[line removed by the dashboard scrubber]\n\nWaiting for stage 1: 1. Waiting for stage 2: 0. Waiting for a third pass: 0. Waiting for a confirmation run: 5.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/queue/CHAMPION.md; echo \"=== STATUS ===\"; cat /home/keith/gemma-v2/wsp31/queue/STATUS.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt"},{"i":9,"kind":"raw","long":false,"text":":(bot-db0a95b5-3607-468f-aba5-423c2ed652b2B!\n\tsessionID\nExamining `STATUS.md` and `RESULTS.md` for clues about the current state. Will focus on the truncated sections of `RESULTS.md` and `STATUS.md`, along with `LEDGER.md` (records 0055, 0056, 0058, 0060, etc.), `TOOLS.md`, `ARCH.md`, and `REPORT.md` to understand the process. The file `cf001-p0` requires close attention during analysis.\n\n\n2(bot-db0a95b5-3607-468f-aba5-423c2ed652b2:\n{\"EndLine\":400,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt\",\"StartLine\":50}:\nI9JA*t,Ys1{65x[n{o\"\u0753r${ /x!St\u697a>CM*vF i&g>\n{\"EndLine\":400,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt\",\"StartLine\":45}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/LEDGER.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read LEDGER.md on wrx90\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/TOOLS.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read TOOLS.md on wrx90\"}Z"},{"i":10,"kind":"raw","long":true,"text":"{\"EndLine\":400,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt\",\"StartLine\":50}:\nI9JA*t,Ys1{65x[n{o\"\u0753r${ /x!St\u697a>CM*vF i&g>\nvC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt\n:\n7Created At: 2026-11-14T15:01:18-05:00\nCompleted At: 2026-11-14T15:01:20-05:00\nShowing lines 50-94 of 94\n50: ## Your parked entries (not screened)\n51: \n52: To put one back as an entry of this round, create an empty file `RESUBMIT` in its queue directory. It is served from the frozen copy, unchanged; a changed edit is a new entry under a new slug.\n53: \n54: - 0017 `late-preedit-commit-gate`: Coordinate-whitened GeGLU late pre-edit commit gate across 13 high-signal layers (dose 1.20)\n55: - 0018 `dual-budget-rescue-r5`: Dual-cap rescue stack: rank-4 exact-close writer subspace (0.38%) plus 13-layer late pre-edit commit gate\n56: \n57: ## Your earlier scored entries\n58: \n59: | ledger | author | slug | title | state | predicted (120) | stage 1 (edit vs reference solved) | stage 2 | verdict |\n60: |---|---|---|---|---|---|---|---|---|\n61: | 0015 | gemini | exact-close-r4-subspace | Spectral rank-4 exact-context within-call thought-close writer subspace across all 60 layers (0.38%) | running_confirm | -4 to +11 | +4.5 (74 vs 72) corrected | +3.5 (control -3.5) | null |\n62: | 0016 | gemini | rumination-damp-r2-net | Subtractive rank-2 deep-rumination attractor damping across all 280 mid-to-late modules (0.36%) | done | -5 to +10 | +0.5 (73 vs 73) | | null |\n[... 27 lines cut ...]\n90: | 0039 | claude | fcv-brief-exact-b20 | Instruction pair vector: think briefly + be exact about what the issue asks, compiled self-consistently into one neuron per layer (dose 2) | queued_confirm | -4 to +8 | +2.0 (79 vs 78) | | null |\n91: | 0047 new | gpt | paired-outcome-writers-r4-100 | Paired outcome writer map across all 60 layers at 1 percent | done | -6 to +12 | -2.5 (75 vs 80) provisional | | null |\n92: | 0048 new | gpt | paired-outcome-writers-r4-033 | Paired outcome writer map across all 60 layers at 0.33 percent | queued_confirm | -4 to +9 | +3.5 (81 vs 80) provisional | | - |\n[line removed by the dashboard scrubber]\n94: | 0050 new | claude | fcv-brief-exact3-b20 | Instruction pair vector, 'be exact about what the issue asks' part written three times in layers 6 to 24, think-briefly part at dose 2 | queued_confirm | -5 to +7 | +4.0 (81 vs 76) provisional | | - |\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nvC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/7/output.txt 2(^05"},{"i":11,"kind":"raw","long":true,"text":"{\"EndLine\":400,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt\",\"StartLine\":45}2\nvC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt\n@\n=Created At: 2026-11-14T15:01:18-05:00\nCompleted At: 2026-11-14T15:01:20-05:00\nShowing lines 45-134 of 134\n45: | 0008 | claude | deep-thought-gate-g3-b03 | done | -4 to +9 | -8.0 (67 vs 73) | | | harmful |\n46: | 0009 | claude | end-neurons-x25 | done | -8 to +9 | -71.0 (3 vs 75) | | | harmful |\n47: | 0010 | claude | early-gate-b01-end-neurons-x9 | parked | -7 to +9 | | | | - |\n48: | 0011 | gpt | writer-close-amplify-033 | done | -7 to +14 | -10.0 (65 vs 73) | | | harmful |\n49: | 0012 | gpt | writer-close-amplify-050 | done | -12 to +16 | -25.5 (44 vs 72) | | | harmful |\n50: | 0013 | gpt | writer-close-shift-011 | parked | -6 to +12 | | | | - |\n51: | 0015 | gemini | exact-close-r4-subspace | running_confirm | -4 to +11 | +4.5 (74 vs 72) | +3.5 | -3.5 | null |\n52: | 0016 | gemini | rumination-damp-r2-net | done | -5 to +10 | +0.5 (73 vs 73) | | | null |\n53: | 0017 | gemini | late-preedit-commit-gate | parked | -3 to +10 | | | | - |\n54: | 0018 | gemini | dual-budget-rescue-r5 | parked | -4 to +14 | | | | - |\n55: | 0020 | claude | net-deep-gate-close-b05 | done | -6 to +8 | -13.5 (58 vs 70) | | | harmful |\n56: | 0021 | claude | net-deep-gate-close-b12 | done | -7 to +9 | -11.5 (60 vs 70) | | | harmful |\n57: | 0022 | claude | net-preedit-commit-b12 | parked | -7 to +7 | | | | - |\n58: | 0023 | claude | net-preedit-commit-close-b05 | parked | -8 to +9 | | | | - |\n[... 71 lines cut ...]\n130: | cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n131: | cf001-p0 | 0031+0015+0044 | 0 | running | 60 | |\n[line removed by the dashboard scrubber]\n133: \n134: Waiting for stage 1: 1. Waiting for stage 2: 0. Waiting for a third pass: 0. Waiting for a confirmation run: 5.\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nvC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/8/output.txt -("},{"i":12,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/LEDGER.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read LEDGER.md on wrx90\"}2\n\\ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/LEDGER.md'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/12/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:01:19-05:00\nCompleted At: 2026-11-14T15:01:22-05:00\nCommand exited with code 0.\n\nCommand output:\n# Ledger index (generated by tools/ledger.py index; do not edit by hand)\n\nRead this before proposing anything. A row marked `null` or `harmful` is not to be retried unless the new\nrecord says what is different and why that difference should matter.\n\n| id | date | author | track | title | set / batch | status | verdict | result |\n|---|---|---|---|---|---|---|---|---|\n| [0001](ledger/0001-claude-unedited-baseline-noise-floor.md) | 2026-11-12 | claude | baseline | Unedited 31B on the screening set, two passes (base rate and identical-arm noise) | wsp31_screen_v1 / s1_base | done | inconclusive | stopped at 59 of 720 episodes; 54% ended at the session limit at concurrency 16 |\n| [0002](ledger/0002-claude-state-of-the-art-survey.md) | 2026-11-12 | claude | survey | Survey of training-free weight editing to November 2026, with 20 ranked edit ideas for 31B | - / - | done | n/a | reports/2026-11-12-weight-editing-survey.md |\n| [0003](ledger/0003-claude-identical-arms-batch-noise-floor.md) | 2026-11-12 | claude | baseline | Three identical-weight arms in one batch (base rate, noise floor, adapter-path check, runner shakedown) | wsp31_screen_v1 / b001 | done | n/a | base 60, aa 60, zero 65 of 120; d 11.3 tasks per identical pair; bars +3 / -6 / +4 / +5 / +10 / -10 |\n[... 90 lines cut ...]\n[line removed by the dashboard scrubber]\n| [0059](ledger/0059-claude-fast2-throughput-deploy.md) | 2026-11-14 | claude | throughput | fast2 deploy - fp8 KV cache, 48 streams and the rest of Son's serving stack on the rented boxes and on wrx90 (changes the numbers; new comparable group) | none (serving change; no task set was run for this record) / none yet; last box batch before fast2 is x008 (or x009 if it forms before the kit commit), last wrx90 batches before are b010 (GPU 1) and b011 (GPU 0); first fast2 batches are named in the Result when they form | running | n/a | deployed without a pass bar at Keith's request; lane's replay measurement 430.0 tok/s against 314.3 for fast1 (+37 %); not yet verified in a real batch |\n[line removed by the dashboard scrubber]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2\\ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/LEDGER.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/12/output.txt"},{"i":13,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/TOOLS.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read TOOLS.md on wrx90\"}2\nJssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/TOOLS.md'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:01:19-05:00\nCompleted At: 2026-11-14T15:01:24-05:00\nCommand exited with code 0.\n\nCommand output:\n# wsp31 tools for edit authors\n\nChangelog (newest first; times US Eastern):\n- Fri 13 Nov, 3:51 PM: **three of the first four edits were harmful (-10 to -21 tasks): read \"Before you submit\"\n (section 5) first.** GPU 0 for pre-tests only while an author turn is open (section 3). New `delimprobe.py`.\n[line removed by the dashboard scrubber]\n 12:39 AM speed (trap 12): **the server's rank limit sets the price of an adapter**.\n- Thu 12 Nov: 11:40 PM first served runs of `dose.py`, `validate.py`, `vgen.py`, `closeprobe.py`; 10:55 PM stacks\n of rank 34 to 96 applied as written; 10:30 PM **thought-end pre-tests need exact contexts**, rank limits 64 or 128\n (never 96); 10:00 PM champion support, network-wide builders; 8:36 PM first version. Earlier commands all still work.\n[... 414 lines cut ...]\n- Any single entry beyond rank 32 per matrix, and edits of norms, `layer_scalar` or embeddings (`overlay.py` exists\n as code, has not been served, and the runner does not accept it).\n- A probe verdict that predicts rollout outcome: the registered ranking test failed on four edits (section 5).\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Jssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/TOOLS.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt"},{"i":14,"kind":"raw","long":false,"text":":(bot-b8520fe7-fd00-4691-9217-520dc23f07aaB!\n\tsessionID\nReading the truncated file contents from `TOOLS.md` and `LEDGER.md` is underway. Also, checking the agent's local directories and ledger entries for relevant context. It's likely that examining these will show the agent's work history or potential leads.\n\n\n2(bot-b8520fe7-fd00-4691-9217-520dc23f07aa:\n{\"EndLine\":300,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt\",\"StartLine\":50}:\n{\"EndLine\":250,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/12/output.txt\",\"StartLine\":20}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/ /home/keith/gemma-v2/wsp31/authors/gemini/queue/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"List code, scratch, and queue dirs\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0060-claude-two-run-rule.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0060 two-run rule\"}Z"},{"i":15,"kind":"raw","long":true,"text":"{\"EndLine\":300,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt\",\"StartLine\":50}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt\nCreated At: 2026-11-14T15:01:34-05:00\nCompleted At: 2026-11-14T15:01:36-05:00\nShowing lines 50-300 of 319\n50: (`dW = -(W v) v^T`) or writes (`dW = -u (u^T W)`); amplify a direction in every reader or writer (section 2).\n51: \n52: Checker (the runner runs exactly this on `edit/` and `ctrl/`, and with `--max-rank 128` on stacked adapters):\n53: \n54: $PY $T/check_adapter.py DIR # CPU. Prints \"OK ...: N modules changed, r=.., max |dW|_F/|W|_F ..\"\n55: \n56: It checks config (LORA, no bias / rslora / dora, base model path, 1 <= r <= 32, alpha == 2 r, target_modules),\n57: tensors (names, shapes, A and B both present, bf16, finite) and a non-zero product somewhere; not whether the edit\n58: is sensible. Cost: 1 s for a small adapter, 2.6 s and 2.5 GB of RAM for rank 128 on all 420 matrices.\n59: **Verified by:** zero adapters reproduce the base model exactly (256/256 decision points, max difference 0.0); 380\n60: single-module adapters (7 module types, layers 0..54) all loaded and all changed the served output; a rank-4\n[line removed by the dashboard scrubber]\n62: points) against 2.15 predicted by this lane's forward pass, correlation 0.986. Rank 32 on all 420 matrices (5% per\n63: matrix): served against forward pass 0.17 at 60 points, as for the unedited model (0.18). Layers 55..59: not run.\n64: \n[... 231 lines cut ...]\n296: 6. **Forward pass beside a server runs out of memory.** Inside a session set `G31_ATT_BUDGET=2.5e8` and keep prompts\n[line removed by the dashboard scrubber]\n298: 7. **fp32 norms are wrong at this size** (1.4% low over 1e8 elements). Use `.double()`.\n299: 8. **Tied embeddings, no biases.** A \"bias\" has to be a neuron that is always on.\n300: 9. **Small edits can vanish in bf16** (8 significant bits): far below 1% of a module's output may round away\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/13/output.txt 2("},{"i":16,"kind":"raw","long":true,"text":"{\"EndLine\":250,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/12/output.txt\",\"StartLine\":20}2\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/12/output.txt\nCreated At: 2026-11-14T15:01:35-05:00\nCompleted At: 2026-11-14T15:01:36-05:00\nShowing lines 20-72 of 72\n20: | [0008](ledger/0008-claude-deep-thought-gate-g3-b03.md) | 2026-11-12 | claude | edit | Deep-thought gate: one neuron per layer 30-48 detects depth >= 800 inside a thought and writes the end-of-thought state (dose 0.3) | wsp31_screen_v1 / b002 | done | harmful | stage 1: -10.0 of 120 tasks |\n[line removed by the dashboard scrubber]\n22: | [0010](ledger/0010-claude-early-gate-b01-end-neurons-x9.md) | 2026-11-12 | claude | edit | Early deep-thought gate (fitted on depth >= 400, dose 0.1) plus own end-of-thought neurons x9: the strong dose of the gated family | wsp31_screen_v1 / - | parked | - | - |\n23: | [0011](ledger/0011-gpt-writer-close-amplify-033.md) | 2026-11-12 | gpt | edit | Amplify natural thought-ending writes across all layers at 0.33 percent | wsp31_screen_v1 / b002 | done | harmful | stage 1: -10.0 of 120 tasks |\n24: | [0012](ledger/0012-gpt-writer-close-amplify-050.md) | 2026-11-12 | gpt | edit | Amplify natural thought-ending writes across all layers at 0.50 percent | wsp31_screen_v1 / b003 | done | harmful | stage 1: -21.0 of 120 tasks |\n25: | [0013](ledger/0013-gpt-writer-close-shift-011.md) | 2026-11-12 | gpt | edit | Shift common writer output toward thought endings across all layers at 0.11 percent | wsp31_screen_v1 / - | parked | - | - |\n26: | [0014](ledger/0014-claude-31b-serving-throughput.md) | 2026-11-12 | claude | throughput | 31B rollout serving speed at fixed quality (server flags, concurrency, LoRA serving cost) | - / - | running | - | rented card, runner batch (4 reference + 2 + 2 edit streams) -19.6% against base only; slots no effect, rank limit 64/128 -5%/-13%; 16-row LoRA expand tile bit-exact at kernel level, gates within self-noise, +5% paired on the runner batch (deploy block DEPLOY.md) |\n27: | [0015](ledger/0015-gemini-exact-close-r4-subspace.md) | 2026-11-12 | gemini | edit | Spectral rank-4 exact-context within-call thought-close writer subspace across all 60 layers (0.38%) | wsp31_screen_v1 / b003, b006 | done | null | both stages: +8.0 (stage 1 +4.5, stage 2 +3.5; control -3.5 on stage 2) |\n28: | [0016](ledger/0016-gemini-rumination-damp-r2-net.md) | 2026-11-12 | gemini | edit | Subtractive rank-2 deep-rumination attractor damping across all 280 mid-to-late modules (0.36%) | wsp31_screen_v1 / x002 | done | null | stage 1: +0.5 of 120 tasks |\n29: | [0017](ledger/0017-gemini-late-preedit-commit-gate.md) | 2026-11-12 | gemini | edit | Coordinate-whitened GeGLU late pre-edit commit gate across 13 high-signal layers (dose 1.20) | wsp31_screen_v1 / - | parked | - | - |\n30: | [0018](ledger/0018-gemini-dual-budget-rescue-r5.md) | 2026-11-12 | gemini | edit | Dual-cap rescue stack: rank-4 exact-close writer subspace (0.38%) plus 13-layer late pre-edit commit gate | wsp31_screen_v1 / - | parked | - | - |\n31: | [0019](ledger/0019-claude-speed-by-rank-limit.md) | 2026-11-13 | claude | tools | Generation speed against the server's LoRA rank limit, and per-stream speed in mixed batches (wrx90) | - / - | done | - | wrx90 GPU 0, 8 streams, n=3 - same rank-32 adapter costs 12% / 13% / 18% of generation speed at rank limit 32 / 64 / 128; rank 96 costs the same as rank 32 at limit 128; unedited streams of a mixed batch are slowed exactly as much as adapter streams |\n32: | [0020](ledger/0020-claude-net-deep-gate-close-b05.md) | 2026-11-13 | claude | edit | Deep-thought gate in all 60 layers: one neuron per layer detects depth >= 800 in a thought and writes the end-of-thought state (per-layer do | wsp31_screen_v1 / b004 | done | harmful | stage 1: -10.5 of 102 tasks |\n33: | [0021](ledger/0021-claude-net-deep-gate-close-b12.md)\n[... 1940 characters cut ...]"},{"i":17,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/ /home/keith/gemma-v2/wsp31/authors/gemini/queue/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"List code, scratch, and queue dirs\"}2\nssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/ /home/keith/gemma-v2/wsp31/authors/gemini/queue/'\nECreated At: 2026-11-14T15:01:35-05:00\nCompleted At: 2026-11-14T15:01:39-05:00\nCommand exited with code 0.\n\nCommand output:\n/home/keith/gemma-v2/wsp31/authors/gemini/code/:\ntotal 948\ndrwxrwxr-x 4 keith keith 4096 Nov 14 13:00 .\ndrwxrwxr-x 5 keith keith 4096 Nov 13 09:13 ..\ndrwxrwxr-x 2 keith keith 4096 Nov 14 12:51 __pycache__\n-rwxr-xr-x 1 keith keith 13755 Nov 13 14:25 analyze_b002_b003.py\n-rwxr-xr-x 1 keith keith 3986 Nov 12 22:56 analyze_probe_sets.py\n-rwxr-xr-x 1 keith keith 10656 Nov 14 07:39 audit_x2_deep.py\n-rwxr-xr-x 1 keith keith 10121 Nov 14 07:38 audit_x2_regime.py\n-rw-r--r-- 1 keith keith 449 Nov 14 12:23 bench_g31_cpu.py\n-rwxr-xr-x 1 keith keith 21086 Nov 12 23:02 capture_gemini_stats.py\n-rwxr-xr-x 1 keith keith 24231 Nov 13 15:17 capture_t5_stats.py\n-rwxr-xr-x 1 keith keith 1147 Nov 14 08:02 check_fro_budget.py\n[... 268 lines cut ...]\n-rw-rw-r-- 1 keith keith 2737 Nov 14 08:49 t9_fp_sel_e2_ctrl.json\ndrwxrwxr-x 2 keith keith 4096 Nov 14 13:00 t9_probes\n-rw-rw-r-- 1 keith keith 66049 Nov 14 08:59 t9_size_dual-audit-postedit-boost.json\n-rw-rw-r-- 1 keith keith 55594 Nov 14 08:58 t9_size_spec-audit-thought-gate.json\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/ /home/keith/gemma-v2/wsp31/authors/gemini/queue/':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/17/output.txt"},{"i":18,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0060-claude-two-run-rule.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0060 two-run rule\"}2\nussh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0060-claude-two-run-rule.md'\nKCreated At: 2026-11-14T15:01:36-05:00\nCompleted At: 2026-11-14T15:01:41-05:00\nCommand exited with code 0.\n\nCommand output:\n---\nid: 0060\ndate: 2026-11-14\nauthor: claude\ntrack: baseline\ntitle: Two-run rule - a 120-task quick screen, then one sealed 300-task run on the boxes that decides (supersedes steps 1-3 of record 0057 for entries not yet judged)\nstatus: done\n[line removed by the dashboard scrubber]\nbatch: none (protocol)\nverdict: n/a\nresult: protocol; run 1 as before (harmful at -6.5 or below, null below +2.0); run 2 = the 300 sealed tasks on the boxes, two unedited arms shared by up to three edits, no control, promote at gain +8.0 or more (1.6 SE, about 5% false pass per candidate); entries already past 0057's screen keep their +5.0 bar\n---\n\n[... 226 lines cut ...]\n difference and cancels. Raw solved counts of the two parts are not compared with each other.\n4. Validity per arm over all 300 tasks, as above (at least 294 clean). A server that dies stops only its part, which\n runs again. An adapter hash mismatch makes the run invalid.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2ussh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0060-claude-two-run-rule.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/18/output.txt"},{"i":19,"kind":"raw","long":false,"text":":(bot-169182cf-8f59-452c-a94d-722f2f781f83B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\n2(bot-169182cf-8f59-452c-a94d-722f2f781f83:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'nvidia-smi --query-gpu=index,memory.used,memory.total,utilization.gpu --format=csv; free -g; ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/data/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/data/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check GPU memory, RAM, and cached data\"}:\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0056-gemini-tri-phase-concise-audit-veto.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0056\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/ARCH.md; echo \\\"=== INTERP REPORT ===\\\"; head -n 120 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ARCH.md and interp/REPORT.md\"}Z"},{"i":20,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'nvidia-smi --query-gpu=index,memory.used,memory.total,utilization.gpu --format=csv; free -g; ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/data/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/data/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check GPU memory, RAM, and cached data\"}:\n&Check GPU memory, RAM, and cached data\nssh -o BatchMode=yes wrx90 'nvidia-smi --query-gpu=index,memory.used,memory.total,utilization.gpu --format=csv; free -g; ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/data/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/data/'\nCreated At: 2026-11-14T15:01:53-05:00\nCompleted At: 2026-11-14T15:01:58-05:00\nCommand exited with code 0.\n\nCommand output:\nindex, memory.used [MiB], memory.total [MiB], utilization.gpu [%]\n0, 94686 MiB, 97887 MiB, 94 %\n1, 90564 MiB, 97887 MiB, 93 %\n total used free shared buff/cache available\nMem: 183 90 9 1 86 93\nSwap: 7 1 6\n/home/keith/gemma-v2/wsp31/authors/gemini/code/data/:\ntotal 217196\ndrwxrwxr-x 2 keith keith 4096 Nov 14 12:54 .\ndrwxrwxr-x 4 keith keith 4096 Nov 14 13:00 ..\n-rw-rw-r-- 1 keith keith 27765650 Nov 12 23:37 gemini_directions.pt\n-rw-rw-r-- 1 keith keith 11307 Nov 12 23:37 gemini_directions.pt.summary.json\n[... 33 lines cut ...]\ntotal 12\ndrwxrwxr-x 3 keith keith 4096 Nov 14 08:40 .\ndrwxrwxr-x 6 keith keith 4096 Nov 14 13:01 ..\ndrwxrwxr-x 2 keith keith 4096 Nov 14 08:40 cache\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'nvidia-smi --query-gpu=index,memory.used,memory.total,utilization.gpu --format=csv; free -g; ls -la /home/keith/gemma-v2/wsp31/authors/gemini/code/data/ /home/keith/gemma-v2/wsp31/authors/gemini/scratch/data/':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/20/output.txt"},{"i":21,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nj\n3Created At: 2026-11-14T15:01:54-05:00\nCompleted At: 2026-11-14T15:02:00-05:00\nCommand exited with code 0.\n\nCommand output:\n---\nid: 0055\ndate: 2026-11-14\nauthor: gemini\ntrack: edit\n[line removed by the dashboard scrubber]\nstatus: done\nset: wsp31_screen_v2\nbatch: x009\nverdict: null\nresult: stage 1: -3.5 of 120 tasks\n---\n[... 91 lines cut ...]\n\n## Verdict and notes\n\nnull by the fixed rule: stage-1 gain -3.5, bar +2, harmful at -6.5 or below.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n[line removed by the dashboard scrubber]\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/21/output.txt"},{"i":22,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0056-gemini-tri-phase-concise-audit-veto.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0056\"}2\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0056-gemini-tri-phase-concise-audit-veto.md'\nHCreated At: 2026-11-14T15:01:55-05:00\nCompleted At: 2026-11-14T15:02:02-05:00\nCommand exited with code 0.\n\nCommand output:\n---\nid: 0056\ndate: 2026-11-14\nauthor: gemini\ntrack: edit\ntitle: Capacity-regularized three-phase GeGLU controller for concise thoughts, post-edit spec audit, and pre-submit veto\nstatus: done\nset: wsp31_screen_v2\nbatch: x009\nverdict: null\nresult: stage 1: -1.5 of 120 tasks\n---\n\n[... 108 lines cut ...]\n\n## Verdict and notes\n\nnull by the fixed rule: stage-1 gain -1.5, bar +2, harmful at -6.5 or below.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0056-gemini-tri-phase-concise-audit-veto.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/22/output.txt"},{"i":23,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/ARCH.md; echo \\\"=== INTERP REPORT ===\\\"; head -n 120 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ARCH.md and interp/REPORT.md\"}2\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/ARCH.md; echo \"=== INTERP REPORT ===\"; head -n 120 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:01:56-05:00\nCompleted At: 2026-11-14T15:02:04-05:00\nCommand exited with code 0.\n\nCommand output:\n# Gemma 4 31B (QAT w4a16) architecture, as served\n\nSource: `config.json` and the safetensors header of `/home/keith/gemma-v2/models/gemma-4-31b-it-qat-w4a16-ct`\n(one file, 23.27 GB, 2009 tensors) and the vLLM 0.19.1 model code that serves it\n(`vllm/model_executor/models/gemma4.py`). The lane's forward pass `g31.py` implements exactly this graph; its\nagreement with the server is measured in `REPORT.md`.\n\n## Sizes\n\n| item | value |\n[... 376 lines cut ...]\n[line removed by the dashboard scrubber]\n fewer in 26; 46 and 22). Not tested: `submit` calls 129, 130, 163, 135; episodes ending with an empty patch 52, 51,\n 41, 46. **For authors:** a \"think briefly\" write is the one mechanism in this programme that has held up on new\n tasks. At a budget of 10,000 it turns about a third of the cut-offs into finished episodes, and that bought too few\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/ARCH.md; echo \"=== INTERP REPORT ===\"; head -n 120 /home/keith/gemma-v2/wsp31/interp/REPORT.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt"},{"i":24,"kind":"raw","long":false,"text":":(bot-e662659e-6cac-4ba0-b2f0-f46cdc9f4af4B!\n\tsessionID\nThe `nvidia-smi` output shows both GPUs are heavily utilized, confirming the suspected workload distribution. Specifically, GPU 0 is running `cf001-p0`, which aligns with the earlier findings from `STATUS.md`. This reinforces the hypothesis that the GPUs are correctly assigned to tasks.\n\n\nGPU 0 is almost fully utilized with a long-running process, suggesting resource constraints. Examining available VRAM and a lock file confirms the GPU's limited capacity. Considering the available CPU RAM and the presence of CPU-specific scripts, it's worth investigating if the workload can shift to the CPU.\n\nIt's crucial to review the comprehensive analysis in `interp/REPORT.md` and `ARCH.md` for potentially critical insights, having previously missed detailed sections in those files.\n\n\n2(bot-e662659e-6cac-4ba0-b2f0-f46cdc9f4af4:\n{\"EndLine\":250,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt\",\"StartLine\":65}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 220 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read top 220 lines of interp/REPORT.md\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0044-gemini-dual-audit-postedit-boost.md; echo \\\"=== 0048 ===\\\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0048-gpt-paired-outcome-writers-r4-033.md; echo \\\"=== 0050 ===\\\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0050-claude-fcv-brief-exact3-b20.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0044, 0048, and 0050\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py; echo \\\"=== t12_cpu_ins.log ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_cpu_ins.log; echo \\\"=== t12_gpu.log ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_gpu.log'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check CPU g31 benchmark and t12 logs\"}Z"},{"i":25,"kind":"raw","long":true,"text":"{\"EndLine\":250,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt\",\"StartLine\":65}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt\nCreated At: 2026-11-14T15:02:13-05:00\nCompleted At: 2026-11-14T15:02:17-05:00\nShowing lines 65-250 of 270\n65: ao = norm_post_attention( o_proj a ) [attn_out]\n66: h = h + ao [resid_mid]\n67: x = norm_pre_feedforward(h) [mlp_in] what gate_proj / up_proj rows read\n68: g = gate_proj x [gate]\n69: u = up_proj x [up]\n70: n = gelu_tanh(g) * u [mlp_act] neuron activations, 21504 per position\n71: y = down_proj n [mlp_raw]\n72: mo = norm_post_feedforward(y) [mlp_out]\n73: h = (h + mo) * layer_scalar [resid_post]\n74: ```\n75: \n[line removed by the dashboard scrubber]\n77: \n78: Rotary encoding: local layers rotate all 128 coordinate pairs `(i, i + 128)` of each head with base 10000. Global\n79: layers use base 1e6 and rotate only the first 64 of 256 pairs `(i, i + 256)`: coordinates 64..255 and 320..511 of a\n[... 166 lines cut ...]\n246: - **The unedited model across batches (descriptive).** Three passes on these 120 tasks at 20,000 (x003, x004, x005,\n247: different rented boxes, same kit): base solved 81, 78, 75, the identical-weights arm 82, 76, 73. Between x003 and x005 the\n248: identical-weights arm lost 11 tasks and gained 2 (p 0.02), base lost 10 and gained 4 (p 0.18). Edits are scored\n249: inside their own batch, so no verdict depends on this; solved counts of different batches must not be compared,\n250: even at one budget. Section 3.8.15; the coordinator checked that kit, harness, task list, zero adapter and\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/23/output.txt A("},{"i":26,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 220 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read top 220 lines of interp/REPORT.md\"}2\n&Read top 220 lines of interp/REPORT.md\nc\nTssh -o BatchMode=yes wrx90 'head -n 220 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/26/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:02:14-05:00\nCompleted At: 2026-11-14T15:02:19-05:00\nCommand exited with code 0.\n\nCommand output:\n# Interpretability lane: what is known about the inside of Gemma 4 31B\n\n[line removed by the dashboard scrubber]\n\n20 of 214, 19 of 225, 27 of 250, 21 of 216). No\n paired test was run on the error rate. Added 7:47 AM ET, Sat 14 Nov 2026: do not read this as an effect of the edits. In batch b008\n the two unedited arms alone had 53 and 32 malformed edit calls (of 359 and 337), a spread as wide as the one\n between reference arms and edits here, and in x004 they had 35 and 44. This lane had no registered prediction for these two entries. Section 3.8.12.\n[... 265 lines cut ...]\n nearest, 0025: 41 cut-offs against 47 and 45, paired p 0.29 and 0.60).\n - Solved 72 | 64 | 77 | 71. A gain is not shown: the two unedited arms differ by 8 (13 tasks lost, 5 gained; 18\n of 120 tasks flip). 0031 against base lost 5 and gained 10 (p 0.30), against the control 4 and 17 (p 0.007);\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Tssh -o BatchMode=yes wrx90 'head -n 220 /home/keith/gemma-v2/wsp31/interp/REPORT.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/26/output.txt"},{"i":27,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0044-gemini-dual-audit-postedit-boost.md; echo \\\"=== 0048 ===\\\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0048-gpt-paired-outcome-writers-r4-033.md; echo \\\"=== 0050 ===\\\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0050-claude-fcv-brief-exact3-b20.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0044, 0048, and 0050\"}2\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0044-gemini-dual-audit-postedit-boost.md; echo \"=== 0048 ===\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0048-gpt-paired-outcome-writers-r4-033.md; echo \"=== 0050 ===\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0050-claude-fcv-brief-exact3-b20.md'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:02:16-05:00\nCompleted At: 2026-11-14T15:02:21-05:00\nCommand exited with code 0.\n\nCommand output:\n---\nid: 0044\ndate: 2026-11-14\nauthor: gemini\ntrack: edit\ntitle: Stateful two-neuron post-edit spec-audit boost with thought and edit-history gating over 180 MLP matrices\nstatus: running\nset: wsp31_screen_v2\nbatch: x006, b011\nverdict: -\n[... 450 lines cut ...]\n\n## Verdict and notes\n\nPending.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0044-gemini-dual-audit-postedit-boost.md; echo \"=== 0048 ===\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0048-gpt-paired-outcome-writers-r4-033.md; echo \"=== 0050 ===\"; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0050-claude-fcv-brief-exact3-b20.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt"},{"i":28,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py; echo \\\"=== t12_cpu_ins.log ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_cpu_ins.log; echo \\\"=== t12_gpu.log ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_gpu.log'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check CPU g31 benchmark and t12 logs\"}2\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py; echo \"=== t12_cpu_ins.log ===\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_cpu_ins.log; echo \"=== t12_gpu.log ===\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_gpu.log'\nCreated At: 2026-11-14T15:02:17-05:00\nCompleted At: 2026-11-14T15:02:23-05:00\nCommand exited with code 0.\n\nCommand output:\nimport os, sys, time\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"\nimport torch\ntorch.set_num_threads(16)\nsys.path.insert(0, \"/home/keith/gemma-v2/wsp31/tools\")\nimport g31\n\nt0 = time.time()\nm = g31.G31(device=\"cpu\", mirror=True, cache_dense=False)\nprint(f\"G31 CPU init: {time.time()-t0:.2f}s\", flush=True)\nt1 = time.time()\nres = m.forward(list(range(1, 2049)), out_pos=[2047], topk=4)\nprint(f\"G31 CPU 2048-tok forward: {time.time()-t1:.2f}s\", flush=True)\n[... 68 lines cut ...]\n [L05 GLOB] o_proj: beta=0.531 r2_oof=0.145 rel=0.18% | down: beta=0.025 r2_oof=0.000 rel=0.01%\n [L11 GLOB] o_proj: beta=0.499 r2_oof=0.089 rel=0.08% | down: beta=0.371 r2_oof=0.032 rel=0.05%\n [L17 GLOB] o_proj: beta=0.501 r2_oof=0.074 rel=0.08% | down: beta=0.114 r2_oof=0.004 rel=0.02%\n [L23 GLOB] o_proj: beta=0.469 r2_oof=0.077 rel=0.08% | down: beta=0.055 r2_oof=0.003 rel=0.02%\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py; echo \"=== t12_cpu_ins.log ===\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_cpu_ins.log; echo \"=== t12_gpu.log ===\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_gpu.log':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/28/output.txt"},{"i":29,"kind":"raw","long":false,"text":":(bot-d24c474b-deb1-46d1-961c-ef943138abb0B!\n\tsessionID\n`bench_g31_cpu.py` reveals a CPU-mode configuration for the process. This suggests the test can run on the CPU. The next step is to determine if the `gpu0.lock` resource is currently held, since this could impact CPU execution, especially if `cf001-p0` is involved.\n\n\n2(bot-d24c474b-deb1-46d1-961c-ef943138abb0:\n{\"EndLine\":350,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\",\"StartLine\":50}:\n{\"EndLine\":700,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\",\"StartLine\":351}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check gpu0.lock and benchmark CPU g31\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0043-gemini-spec-audit-thought-gate.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0043\"}Z"},{"i":30,"kind":"raw","long":true,"text":"{\"EndLine\":350,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\",\"StartLine\":50}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\nCreated At: 2026-11-14T15:02:41-05:00\nCompleted At: 2026-11-14T15:02:43-05:00\nShowing lines 50-350 of 371\n50: - **Pre-test diagnostics on unseen `safe_s1` episodes** *(note: per `TOOLS.md`, probe verdict words/thresholds are not calibrated to rollout task gains)*:\n51: - Offline exact forward pass (`t9_hold1.py`, 14 unseen calls): highest full-vocab thought log-prob shift alignment with `P_audit` (`cos = +0.352`), positive post-edit KL recovery (`+0.0005`), and `0 / 124` top-1 flips on `<|\"|>` delimiters and JSON tool arguments.\n52: - Served `fastprobe.py` on `held26_ep.jsonl` (port [port], 455 decision points of 20 unseen `safe_s1` traces):\n53: - `edit`: `ACTIVE`, `mean KL = 0.00169` (`max 0.0431`; `turn 0.00028`, `step 0.00318`, `think 0.00085`, `tool 0.00130`), `0.0%` protocol-boundary top-1 flips (`P(<|channel>) 0.998->0.998` at `turn`, `P(<|tool_call>) 0.962->0.961` at `think`).\n54: - `ctrl`: `ACTIVE`, `mean KL = 0.00114` (`max 0.0376`; `turn 0.00018`, `step 0.00180`, `think 0.00101`, `tool 0.00078`), `0.0%` protocol-boundary top-1 flips.\n55: \n56: Runner facts (2026-11-14 09:00:14 EST): source `wsp31/authors/gemini/queue/dual-audit-postedit-boost/`; served copy `wsp31/queue/frozen/gemini__dual-audit-postedit-boost/`; sha256 over files, edit `9cc55905b8077258080faafecb870e5cd88e3b8b6076e3e3c8909016da5dc5c4`, control `6e4286cddf107f587633f64b37bd902a185c260b015c5666e21ce7d7cb0b3630`; both passed the checker.\n57: \n58: ## Prediction (written before the run)\n59: \n60: predicted_gain_120: 3.0 to 8.5\n61: \n[line removed by the dashboard scrubber]\n63: 1. Stateful post-edit verification without pre-edit slowdown: pre-edit tool calls to first `edit_file` remain as fast as unedited `base/aa` (because `j_1` stays `~10x` quieter before `edit_file`), while post-edit turns add targeted boundary-case `run_command` tests and edge-case `edit_file` refinements prior to `submit_patch`, cutting `wrong_clean` failures by `4 to 9` tasks.\n[line removed by the dashboard scrubber]\n[... 281 lines cut ...]\n346: 0039 27). This is the number the entry is for.\n347: - median tool calls about 19 against 21 to 22.\n348: \n[line removed by the dashboard scrubber]\n350:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt 2("},{"i":31,"kind":"raw","long":false,"text":"{\"EndLine\":700,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\",\"StartLine\":351}2\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\nCreated At: 2026-11-14T15:02:41-05:00\nCompleted At: 2026-11-14T15:02:43-05:00\nShowing lines 351-371 of 371\n351: The hypothesis is wrong if the finished-wrong count is 30 or more (three times the I5 part did not even hold 0039's\n352: level) or the gain is at or below 0038's -2: then 0039 minus 0038 was noise, a constant vector does not carry a\n353: quality instruction, and I stop varying constants. It is unproven if the gain is 0 to +3 with finished-wrong 25 to 29.\n354: A gain of +5 or more with finished-wrong at 24 or below would be a dose response and worth a stage 2.\n355: A drop in solved by 6 or more with more tool calls or longer thoughts means the mid-layer overshoot (risk 1) broke\n356: ordinary behaviour.\n357: \n358: ## Result\n359: \n[line removed by the dashboard scrubber]\n361: \n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n365: - edit against the mean of the two reference arms: +4.0 tasks of 120 (95% interval -1.0 to +9.5).\n366: - Predicted gain -5 to +7; measured +4.0: inside the interval.\n367: - Gain +4.0 is at or above the stage-1 bar (+2): goes to stage 2 with its control.\n368: \n369: ## Verdict and notes\n370: \n371: Pending.\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/27/output.txt"},{"i":32,"kind":"raw","long":false,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check gpu0.lock and benchmark CPU g31\"}2\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\n}file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\n&GPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\"\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py':%Check gpu0.lock and benchmark CPU g31B\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py'\nuCommand exited with code 0.\n\nCommand output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\nG31 CPU 2048-tok forward: 190.06s\nterminalJ'\n%check gpu0.lock and benchmark CPU g31R\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py'\n\"HGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\nG31 CPU 2048-tok forward: 190.06s\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/32/output.txt"},{"i":33,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0043-gemini-spec-audit-thought-gate.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read ledger 0043\"}2\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0043-gemini-spec-audit-thought-gate.md'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/33/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:02:43-05:00\nCompleted At: 2026-11-14T15:02:57-05:00\nCommand exited with code 0.\n\nCommand output:\n---\nid: 0043\ndate: 2026-11-14\nauthor: gemini\ntrack: edit\ntitle: Thought-gated reliability-shrunk Problem Statement spec-audit steering across all 60 MLP layers\nstatus: done\nset: wsp31_screen_v2\nbatch: x006\nverdict: null\n[... 133 lines cut ...]\n\n## Verdict and notes\n\nnull by the fixed rule: stage-1 gain +2.5, bar +3, harmful at -6 or below.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger/0043-gemini-spec-audit-thought-gate.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/33/output.txt"},{"i":34,"kind":"raw","long":false,"text":":(bot-627c20c0-162f-4201-874b-fe58bb6a411cB!\n\tsessionID\nExamining the background task `task-32` and `x009` simultaneously for insights. Reviewing `RESULTS.md` for `x009`, specifically entries `0055` and `0056`, based on behavioral counters. Focus now is on understanding the `x009`'s counters.\n\n\nAnalyzing counter data for `x009` reveals significant performance improvements in specific configurations. `0055` demonstrates a dramatic reduction in session limits and median tool calls compared to the base configuration, with a slight decrease in solved tasks. `0056` also shows improvements in session limits and tool calls, though less drastic, and with a similar task count.\n\nThese results suggest an improved approach within these specific configurations, but require further investigation to understand the cause of reduced errors and tool call efficiency. Focusing on the differences in these two configurations appears crucial.\n\n\n2(bot-627c20c0-162f-4201-874b-fe58bb6a411c:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/PRIOR_E4B.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read PRIOR_E4B.md on wrx90\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md; echo \\\"=== SECTION C ===\\\"; grep -n \\\"^##\\\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read weight-editing survey sections\"}Z"},{"i":35,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}:\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nCreated At: 2026-11-14T15:03:08-05:00\nCompleted At: 2026-11-14T15:03:15-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\nLog output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\nLast progress: 19s ago\ntasksJ'\n%Check gpu0.lock and benchmark CPU g31Rc\na**Status**: RUNNING \u2022 **Last progress**: 19s ago\n\n```\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n```2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/35/output.txt"},{"i":36,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/PRIOR_E4B.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read PRIOR_E4B.md on wrx90\"}2\n_ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/PRIOR_E4B.md'\nH\n\"Created At: 2026-11-14T15:03:09-05:00\nCompleted At: 2026-11-14T15:03:17-05:00\nCommand exited with code 0.\n\nCommand output:\n# What was already tried on Gemma 4 E4B (paper track, 4-12 Nov 2026)\n\nThese are training-free weight edits on the small model, written by Claude, GPT and Gemini, measured on 170\n[line removed by the dashboard scrubber]\nonly for 31B) and on 130 held-out tasks. Sources: the private paper repository (`gemma-weight-programming`), its\nexperiment log and result files. Counts are tasks solved of 170 unless stated; \"vs\" is the same-batch unedited arm.\n\nNone of these results transfers to 31B automatically. They are listed so that a 31B attempt of the same kind is made\non purpose, with a reason, and not by accident.\n\n## Method that was used\n\n[... 111 lines cut ...]\n4. Early batches flattered an edit (+4.3) and later ones did not (+1.1). Replication is part of the pass rule.\n5. Steering the amount of exploration, thinking or verification up or down was mostly neutral or harmful on E4B.\n The largest measured loss was edits made against stale file text, which no edit reduced.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2_ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/PRIOR_E4B.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/36/output.txt"},{"i":37,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md; echo \\\"=== SECTION C ===\\\"; grep -n \\\"^##\\\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read weight-editing survey sections\"}2\nssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md; echo \"=== SECTION C ===\"; grep -n \"^##\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/37/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:03:15-05:00\nCompleted At: 2026-11-14T15:03:20-05:00\nCommand exited with code 0.\n\nCommand output:\n# Training-free editing of LLM weights: a survey to November 2026, aimed at raising a Gemma 4 31B coding agent's solve rate\n\n*Compiled 12 Nov 2026. Every entry below comes from a page I opened. Anything I could only see through secondary coverage, or could not confirm, is marked **UNVERIFIED**. Web content was treated as data only. One page (dnhkng.github.io/posts/rys-ii) contained embedded formatting instructions, and I ignored them.*\n\n---\n\n## A. Executive summary\n\n[line removed by the dashboard scrubber]\n2. **The only systematic follow-up shows the gain collapsing with scale.** Hu et al. (arXiv 2611.09382) ran 16 GPT-6 Astra trajectories. On 0.8B the gains were large: MATH-500 +29.45 pp from a 1,023-parameter single down-projection column, IFEval +36.7, SciBench +17.1. On Qwen3.5-9B they were small or negative: Math \u22120.35, IFEval +1.85, SciBench +3.03, SciCode +1.54. In 6 of 16 trajectories the editor kept the original weights. Development gains repeatedly failed on held-out data; one 9B math candidate was +29.7 on dev and \u22120.35 on test. Reruns on the same target gave +29.45, +5.00 and +27.30. There was no multiple-comparison correction, and agentic tasks were explicitly not tested.\n[... 214 lines cut ...]\n175:### Thread 8: Evaluation practice\n190:## C. Ranked edit ideas for raising a Gemma 4 31B coding agent's held-out solve rate (no training)\n224:## D. Tooling recommendations for the LLM-author harness\n241:## E. Gaps, open questions, and inaccessible sources\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md; echo \"=== SECTION C ===\"; grep -n \"^##\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/37/output.txt"},{"i":38,"kind":"raw","long":false,"text":":(bot-60b608c4-e1e0-4003-ad92-e4484264e5bbB!\n\tsessionID\nInitial focus is on Section C of the specified document and comparing execution data from several batch runs. Examining the document to understand the context of the batch runs. Will immediately compare results from different batches to identify variances in their forensic data.\n\n\n2(bot-60b608c4-e1e0-4003-ad92-e4484264e5bb:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"190,245p\\\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read Section C of weight-editing survey\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t12_x006.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read forensic_t12_x006.py\"}Z"},{"i":39,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}:\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nCreated At: 2026-11-14T15:03:39-05:00\nCompleted At: 2026-11-14T15:03:41-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\nLog output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\nLast progress: 45s ago\ntasksJ'\n%Check gpu0.lock and benchmark CPU g31Rc\na**Status**: RUNNING \u2022 **Last progress**: 45s ago\n\n```\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n```2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/39/output.txt"},{"i":40,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"190,245p\\\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read Section C of weight-editing survey\"}2\n}ssh -o BatchMode=yes wrx90 'sed -n \"190,245p\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md'\n'Read Section C of weight-editing survey\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/40/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:03:40-05:00\nCompleted At: 2026-11-14T15:03:43-05:00\nCommand exited with code 0.\n\nCommand output:\n## C. Ranked edit ideas for raising a Gemma 4 31B coding agent's held-out solve rate (no training)\n\nRanking is by my estimate of expected held-out gain times probability of a clean confirmation. That estimate is mine, not a sourced figure. \"Bake\" means compile into your rank-32 LoRA-shaped adapter or a gated quiet-neuron write.\n\n| # | Idea | Motivating source | Data needed | Risk |\n|---|---|---|---|---|\n| 1 | **Bake TACT's overthinking and overacting axes with a band gate.** Fit OT-vs-CAL and OA-vs-CAL (orthogonalised) at `` (end of thought) on judge-labelled steps. Implement TACT-Gate's \"subtract excess beyond calibrated band\" as a one-sided gated neuron per top-AUC layer (a GeGLU gate gives a soft threshold). Verify hook-vs-baked equivalence first | TACT (+4.8 avg on Gemma-4-26B-A4B; random and shuffled controls \u22640) | Your failure traces, chunk-labelled by a frontier judge (TACT spent ~$600 for 2k trajectories); activations at end-of-thought | Medium. Only TACT's own evidence; ~3.2% harmful flips; a soft gate is an approximation of the hook |\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[... 99 lines cut ...]\n**Gaps (what nobody has shown, as far as I could find)**\n- An LLM-authored *baked* edit raising *held-out agentic coding* solve rate at \u226527B with matched controls and multiple runs. TACT is hook-based with no seeds. Concept Country is single-turn and human-directed. WSP is untested on agents and shrinks at 9B.\n- Whether WSP-style edits add capability at all, rather than removing a blocker. Every positive result so far is a loop or overthinking fix, or a format or instruction-following fix.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2}ssh -o BatchMode=yes wrx90 'sed -n \"190,245p\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/40/output.txt"},{"i":41,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t12_x006.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read forensic_t12_x006.py\"}2\ndssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t12_x006.py'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:03:41-05:00\nCompleted At: 2026-11-14T15:03:46-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Exact Turn 12 CPU forensic analysis of x006 (base, aa, e0043, e0044) and x003..x006 x2 arms.\nStrictly Stage-2-disjoint (excludes all stage2*.txt IDs).\n\"\"\"\nimport json\nimport pathlib\nimport statistics\nimport subprocess\nimport sys\nfrom collections import Counter\n[... 454 lines cut ...]\n\nif __name__ == \"__main__\":\n main()\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2dssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t12_x006.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt"},{"i":42,"kind":"raw","long":false,"text":":(bot-f412ebe4-2d47-4785-a118-04edc6146d01B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\n2(bot-f412ebe4-2d47-4785-a118-04edc6146d01:\n{\"EndLine\":190,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt\",\"StartLine\":105}:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}Z"},{"i":43,"kind":"raw","long":true,"text":"{\"EndLine\":190,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt\",\"StartLine\":105}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt\n#\n Created At: 2026-11-14T15:03:55-05:00\nCompleted At: 2026-11-14T15:03:56-05:00\nShowing lines 105-190 of 263\n105: pre_calls += 1\n106: \n107: comp_toks = out_toks\n108: thought_toks = 0\n109: pre_toks = 0\n110: post_toks = 0\n111: unpaired_52 = 0\n112: no_tool_calls = 0\n113: \n114: if parse_reqs and rpath.exists():\n115: comp_toks = 0\n116: reqs = [json.loads(l) for l in rpath.read_text().splitlines() if l.strip()]\n117: for ci, req in enumerate(reqs):\n[line removed by the dashboard scrubber]\n[... 67 lines cut ...]\n186: f\"med_toks={statistics.median(v['comp_toks'] for v in vals):.0f} \"\n187: f\"(pre={statistics.median(v['pre_toks'] for v in vals):.0f}, post={statistics.median(v['post_toks'] for v in vals):.0f}), \"\n188: f\"med_thought={statistics.median(v['thought_toks'] for v in vals):.0f}\")\n189: print(f\" Post-edit behavior: mean_post_run={statistics.mean(v['n_post_run'] for v in vals):.2f}, \"\n190: f\"mean_py_c={statistics.mean(v['n_post_py_c'] for v in vals):.2f}, \"\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/41/output.txt i("},{"i":44,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}2\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nCreated At: 2026-11-14T15:03:56-05:00\nCompleted At: 2026-11-14T15:03:56-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\nLog output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\nLast progress: 1m0s ago\ntasksJ'\n%Check gpu0.lock and benchmark CPU g31Rd\nb**Status**: RUNNING \u2022 **Last progress**: 1m0s ago\n\n```\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n```2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/44/output.txt"},{"i":45,"kind":"raw","long":false,"text":":(bot-0d8dbcdd-823d-4946-a4ae-a7b20268b081B!\n\tsessionID\nRunning the task in the background to capture wall-clock timing is critical for benchmarking. A local Python script will be created to perform the forensic analysis.\n\n\nThe Python script will be transferred to a remote machine for execution and analysis. The script's primary objective is to identify and quantify specific error categories across different test configurations, focusing on discrepancies in performance metrics, especially those with significant drops in session limits or tool call counts. Further investigation will involve examining request and trace data to pinpoint the root causes of performance changes, particularly focusing on how these shifts affect output scores, especially when comparing runs across different configurations.\n\n\nAnalyzing performance across multiple batches, including identifying specific tasks that exhibit consistent failure or unique success patterns. Investigating traces of consistently failing and uniquely successful tasks to identify root causes related to performance changes. Consolidating the analysis by comparing performance across all unedited runs, aiming to find common performance issues.\n\n\n2(bot-0d8dbcdd-823d-4946-a4ae-a7b20268b081:\n[line removed by the dashboard scrubber]"},{"i":46,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n:C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\forensic_t15_x009.py\nh\nh#!/usr/bin/env python3\n\"\"\"Turn 15 Stage-2-safe forensic analysis across x009, x008, b010, x006, and all 14 unedited x2 reference runs.\"\"\"\nimport json\nimport pathlib\nimport statistics\nfrom collections import Counter\n\nR = pathlib.Path(\"/home/keith/gemma-v2\")\nSETS = R / \"wsp31/queue/sets\"\nBATCHES = R / \"results/wsp31/batches\"\n\n\ndef load_safe_sets():\n s2all = set()\n for p in SETS.glob(\"stage2*.txt\"):\n s2all |= {x.strip() for x in p.read_text().splitlines() if x.strip()}\n s1 = {x.strip() for x in (SETS / \"stage1_ids.txt\").read_text().splitlines() if x.strip()}\n[... 638 lines cut ...]\n; tids_p = [iid for iid in tids if iid in st]\nG\nC s = sum(1 for iid in tids_p if st[iid][\"resolved\"])\n@\n< vals_str.append(f\"{s:4d}/{len(tids_p):<5d}\")\nL\nH print(f\"{bname:12s} | {len(tids):3d} | \" + \" | \".join(vals_str))\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/46/output.txt"},{"i":47,"kind":"raw","long":false,"text":":(bot-a3309f95-50b2-4168-92ec-2ccbb7fb477aB!\n\tsessionID\n2(bot-a3309f95-50b2-4168-92ec-2ccbb7fb477a:\n{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\forensic_t15_x009.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run forensic_t15_x009.py on wrx90\"}:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}`"},{"i":48,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\forensic_t15_x009.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run forensic_t15_x009.py on wrx90\"}:\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\n}file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-48.log\"\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\forensic_t15_x009.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py':!Run forensic_t15_x009.py on wrx90B\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\forensic_t15_x009.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCommand exited with code 0.\n\nCommand output:\nsafe_v2=120, valid119=119\nx003/base | N=119 SOLV=81 WC=24 CUT= 6 EMP= 8 | toks= 7461 th~=5317 calls=21.0(pre=9.0,post=10.0) read= 8.8 run=14.7 edit=2.34(fail=0.90) noTC=223 testAfter=104 u52=1.00%\nx003/aa | N=119 SOLV=82 WC=22 CUT= 9 EMP= 6 | toks= 7338 th~=5550 calls=23.0(pre=9.0,post=9.0) read= 8.2 run=15.2 edit=2.51(fail=1.03) noTC=215 testAfter=108 u52=0.75%\nx003/e0035 | N=119 SOLV=79 WC=27 CUT= 8 EMP= 5 | toks= 8424 th~=5736 calls=20.0(pre=9.0,post=9.0) read= 8.2 run=14.5 edit=2.45(fail=0.79) noTC=222 testAfter=110 u52=0.81%\nx003/e0036 | N=119 SOLV=78 WC=20 CUT=15 EMP= 6 | toks= 8011 th~=5570 calls=24.0(pre=10.0,post=10.0) read= 9.7 run=15.7 edit=2.19(fail=0.82) noTC=227 testAfter=107 u52=1.07%\n-------------------------------------------------------------------------------------------------------------------------------------------------\nx004/base | N=119 SOLV=78 WC=27 CUT= 8 EMP= 6 | toks= 8231 th~=5213 calls=22.0(pre=9.0,post=9.0) read= 8.1 run=15.3 edit=2.24(fail=0.77) noTC=236 testAfter=110 u52=0.54%\nx004/aa | N=119 SOLV=76 WC=28 CUT= 8 EMP= 7 | toks= 7915 th~=5313 calls=21.0(pre=9.0,post=10.0) read= 8.1 run=15.1 edit=2.29(fail=0.86) noTC=227 testAfter=109 u52=0.76%\nx004/e0038 | N=119 SOLV=75 WC=33 CUT= 6 EMP= 5 | toks= 6279 th~=4117 calls=19.0(pre=9.0,post=9.0) read= 7.5 run=14.2 edit=2.34(fail=0.76) noTC=240 testAfter=111 u52=0.64%\n[... 186 lines cut ...]\n1-25% | 7 | 0.79 | 0/7 | 1/7 | 1/7 | 2/7 | 3/7 | 0/7 \n25-60% | 11 | 4.43 | 5/11 | 6/11 | 6/11 | 4/11 | 3/11 | 7/11 \n60-85% | 8 | 5.71 | 6/8 | 6/8 | 7/8 | 7/8 | 7/8 | 7/8 \n85-100% | 68 | 66.93 | 68/68 | 67/68 | 66/68 | 68/68 | 65/68 | 66/68 \n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\forensic_t15_x009.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/forensic_t15_x009.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt"},{"i":49,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}2\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nCreated At: 2026-11-14T15:05:00-05:00\nCompleted At: 2026-11-14T15:05:13-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\nLog output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\nLast progress: 2m17s ago\ntasksJ'\n%Check gpu0.lock and benchmark CPU g31Re\nc**Status**: RUNNING \u2022 **Last progress**: 2m17s ago\n\n```\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n```2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/49/output.txt"},{"i":50,"kind":"raw","long":false,"text":":(bot-67cd8721-f4b4-4b3d-92fd-1756186ed1eaB!\n\tsessionID\nA single forward pass, even with a relatively small model like this, is extremely slow on CPU. This suggests the dequantization and matrix operations are heavily bottlenecked. Reviewing the related code suggests possible optimization opportunities in the Python implementation itself.\n\n\n2(bot-67cd8721-f4b4-4b3d-92fd-1756186ed1ea:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/tools/g31.py; echo \\\"=== t9_build.py ===\\\"; head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_build.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read g31.py and t9_build.py\"}:"},{"i":51,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/tools/g31.py; echo \\\"=== t9_build.py ===\\\"; head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_build.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read g31.py and t9_build.py\"}:\nssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/tools/g31.py; echo \"=== t9_build.py ===\"; head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_build.py'\nICreated At: 2026-11-14T15:05:21-05:00\nCompleted At: 2026-11-14T15:05:24-05:00\nCommand exited with code 0.\n\nCommand output:\n\"\"\"g31: loader, dequantiser and hooked dense forward pass for Gemma 4 31B (QAT w4a16, compressed-tensors\npack-quantized checkpoint), written to mirror what vLLM 0.19.1 computes when it serves that checkpoint with\n--dtype bfloat16 (vllm/model_executor/models/gemma4.py). Library for the wsp31 tools lane; see ARCH.md and REPORT.md.\n\nConventions: \"mod\" is one of q_proj k_proj v_proj o_proj gate_proj up_proj down_proj. Global (full-attention)\nlayers have no v_proj tensor in the checkpoint: vLLM loads k_proj into both the K and the V slot, so\nweight(l, \"v_proj\") returns the k_proj weight there. All weights are returned as bf16 [out, in].\n\"\"\"\nimport json\nimport math\nimport os\nimport struct\n\n[... 466 lines cut ...]\n d_col = d_raw * (eta_eff / eta_lin)\n\n g_actual = (ab / (sig * ((1.0 + eta_eff * eta_eff) ** 0.5))) * (w_post * d_col)\n rem_after_sl = sl * (g_want - g_actual)\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/tools/g31.py; echo \"=== t9_build.py ===\"; head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_build.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/51/output.txt"},{"i":52,"kind":"raw","long":false,"text":":(bot-66576b47-467d-476a-81eb-e54032f813e6B!\n\tsessionID\nExamining `task-48` and `task-32` to understand execution characteristics. Further investigation of `g31.py` focuses on lines 121-260 to clarify the performance difference between `cache_dense=False` versus `cache_dense=True` or batched CPU forward processing.\n\n\n2(bot-66576b47-467d-476a-81eb-e54032f813e6:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\"}:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"121,280p\\\" /home/keith/gemma-v2/wsp31/tools/g31.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read lines 121-280 of g31.py\"}Z"},{"i":53,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\"}:\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\nCreated At: 2026-11-14T15:05:30-05:00\nCompleted At: 2026-11-14T15:05:31-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-48.log\ntasksJ#\n!Run forensic_t15_x009.py on wrx90R4\n2**Status**: RUNNING\n\n*No log output recorded yet.*2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/53/output.txt"},{"i":54,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}2\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nCreated At: 2026-11-14T15:05:30-05:00\nCompleted At: 2026-11-14T15:05:31-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\nLog output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\nLast progress: 2m35s ago\ntasksJ'\n%Check gpu0.lock and benchmark CPU g31Re\nc**Status**: RUNNING \u2022 **Last progress**: 2m35s ago\n\n```\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n```2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/54/output.txt"},{"i":55,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"121,280p\\\" /home/keith/gemma-v2/wsp31/tools/g31.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read lines 121-280 of g31.py\"}2\nVssh -o BatchMode=yes wrx90 'sed -n \"121,280p\" /home/keith/gemma-v2/wsp31/tools/g31.py'\n~\n=Created At: 2026-11-14T15:05:31-05:00\nCompleted At: 2026-11-14T15:05:34-05:00\nCommand exited with code 0.\n\nCommand output:\n\nclass G31:\n \"\"\"Packed 31B language-model weights on one GPU plus a hooked forward pass.\n\n Holds the int4 words and scales (about 16 GB) and dequantises each layer when it is used, so it fits beside a\n vLLM server. `mirror=True` (default) rounds activations to bf16 at the points where vLLM does; `mirror=False`\n keeps fp32 activations (bf16-valued weights), which is the cleaner reference for interpretability work.\n \"\"\"\n\n def __init__(self, device=\"cuda:0\", model_dir=MODEL_DIR, mirror=True, cache_dense=False, layers=None):\n from safetensors import safe_open\n self.arch = Arch(model_dir)\n[... 307 lines cut ...]\n[line removed by the dashboard scrubber]\n\n[line removed by the dashboard scrubber]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2Vssh -o BatchMode=yes wrx90 'sed -n \"121,280p\" /home/keith/gemma-v2/wsp31/tools/g31.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/55/output.txt"},{"i":56,"kind":"raw","long":false,"text":":(bot-cd3c067d-bbaa-4cad-9dd5-f87a829bbab9B!\n\tsessionID\nThe memory requirements for `cache_dense=True` on the CPU are 58.6 GB of bf16 RAM, and the system has 93 GB available. This suggests the CPU configuration should be sufficient, which contradicts the initial error.\n\n\nThe CPU memory appears sufficient, but the core processing strategy might be inefficient. Processing the matrices for a single prompt at a time involves dequantizing and multiplying a large number of elements repeatedly. Considering layer-by-layer processing across multiple prompts, the dequantization overhead is amortized across all prompts. The matrix dequantization time can be optimized using the maximum cores. Given this, it may be possible to evaluate 24 prompts simultaneously without increasing memory overhead.\n\n\n2(bot-cd3c067d-bbaa-4cad-9dd5-f87a829bbab9:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\"}:\nK{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}Z"},{"i":57,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\"}:\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\nCreated At: 2026-11-14T15:05:44-05:00\nCompleted At: 2026-11-14T15:05:45-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-48.log\ntasksJ#\n!Run forensic_t15_x009.py on wrx90R4\n2**Status**: RUNNING\n\n*No log output recorded yet.*2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/57/output.txt"},{"i":58,"kind":"raw","long":false,"text":"K{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\"}2\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nCreated At: 2026-11-14T15:05:45-05:00\nCompleted At: 2026-11-14T15:05:45-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\nStatus: RUNNING\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\nLog output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n\nLast progress: 2m49s ago\ntasksJ'\n%Check gpu0.lock and benchmark CPU g31Re\nc**Status**: RUNNING \u2022 **Last progress**: 2m49s ago\n\n```\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\n```2n\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/58/output.txt"},{"i":59,"kind":"raw","long":false,"text":":(bot-4d0ba630-e8e3-4d98-a2f6-9a387e60412eB!\n\tsessionID\nInitial hypothesis: Long-running command might be causing the delay. Checking if the system treats the command as a background task. If it's running in the background, a timeout isn't the issue.\n\n\n2(bot-4d0ba630-e8e3-4d98-a2f6-9a387e60412e:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_build.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_build.py on wrx90\"}:\n[line removed by the dashboard scrubber]"},{"i":60,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_build.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_build.py on wrx90\"}:\n\\ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_build.py'\nPThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:05:52-05:00\nCompleted At: 2026-11-14T15:05:57-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Deterministic CPU weight-edit builder for Turn 12 (author: gemini).\n\nSupports two training-sized closed-form architectures rebuilt bit-for-bit on CPU in <6s:\n1. `tri_phase`: Capacity-regularized 3-neuron stateful GeGLU episode controller (`r=3`, 180 MLP matrices `0..59`)\n with focus/anti-rumination (`j_0`), post-edit spec-audit (`j_1`), and pre-submit diff-veto (`j_2`).\n[line removed by the dashboard scrubber]\n `o_proj` + `down_proj` across `5..58`) with SVD-spectrum-identical, syntax-nullspace-preserving orthogonal control.\n\"\"\"\nimport argparse\n[... 791 lines cut ...]\n\nif __name__ == \"__main__\":\n main()\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2\\ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_build.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt"},{"i":61,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY -c \"\nimport torch, pathlib\nd = pathlib.Path(\\\"/home/keith/gemma-v2/wsp31/authors/gemini/code/data\\\")\nfor fn in sorted(d.glob(\\\"*.pt\\\")):\n obj = torch.load(fn, map_location=\\\"cpu\\\", weights_only=False)\n print(\\\"===\\\", fn.name, \\\"===\\\")\n if isinstance(obj, dict):\n for k, v in obj.items():\n if hasattr(v, \\\"shape\\\"):\n print(f\\\" {k}: Tensor{tuple(v.shape)} {v.dtype}\\\")\n elif isinstance(v, dict):\n[line removed by the dashboard scrubber]\n elif isinstance(v, list):\n print(f\\\" {k}: list(len={len(v)})\\\")\n else:\n print(f\\\" {k}: {type(v).__name__}={str(v)[:80]}\\\")\n\"'\nCreated At: 2026-11-14T15:05:54-05:00\nCompleted At: 2026-11-14T15:06:00-05:00\n[... 36 lines cut ...]\n elif isinstance(v, dict):\n[line removed by the dashboard scrubber]\n elif isinstance(v, list):\n print(f\\\" {k}: list(len={len(v)})\\\")\n else:\n print(f\\\" {k}: {type(v).__name__}={str(v)[:80]}\\\")\n\"':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/61/output.txt"},{"i":62,"kind":"raw","long":false,"text":"[Message] timestamp=2026-11-14T20:05:58Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\" finished with result:\nCommand exited with code 0.\n\nCommand output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\nG31 CPU 2048-tok forward: 190.06s\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log\n.Check gpu0.lock and benchmark CPU g31 finishedR\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py'\n\"HGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\nG31 CPU 2048-tok forward: 190.06s\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32(\nR0\n.Check gpu0.lock and benchmark CPU g31 finishedb\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; flock -n $R/wsp31/gpu0.lock echo GPU0_LOCK_FREE || echo GPU0_LOCK_HELD; nproc; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_g31_cpu.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check gpu0.lock and benchmark CPU g31\"}\"\nTask id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-32\" finished with result:\nCommand exited with code 0.\n\nCommand output:\nGPU0_LOCK_HELD\n48\nG31 CPU init: 0.02s\nG31 CPU 2048-tok forward: 190.06s\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-32.log"},{"i":63,"kind":"raw","long":false,"text":":(bot-c0628479-a198-4a0a-99ad-9ed0433e1856B!\n\tsessionID\nTask 32 finished, and the initial test of dequantizing matrices for a single sequence took 190 seconds. Processing 32 sequences concurrently, layer by layer, could optimize this by dequantizing matrices for only those sequences.\n\n\n2(bot-c0628479-a198-4a0a-99ad-9ed0433e1856:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_phase_a_g31.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_phase_a_g31.py on wrx90\"}:\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\inspect_pts.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect all .pt files in code/data\"}Z"},{"i":64,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_phase_a_g31.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_phase_a_g31.py on wrx90\"}:\njssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_phase_a_g31.py'\na\n.Created At: 2026-11-14T15:06:11-05:00\nCompleted At: 2026-11-14T15:06:16-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Turn 12 Phase A \u2014 Offline GPU-0 g31 Capture, Fit & Unseen Held-Out Verification (author: gemini).\n\nRuns under `flock /home/keith/gemma-v2/wsp31/gpu0.lock` BEFORE starting vLLM so G31 has clean GPU-0 memory\nand releases 100% of VRAM upon process exit before Phase B (`gpu0_session.sh 18420`).\n\nSteps:\n1. Builds `scratch/t12_probes/held26_submit_calls.jsonl` (exact unseen safe_s1 submit_patch calls, zero Stage-2 contact).\n2. Runs base + 3 incremental teacher passes (`P_FOCUS`, `P_FOCUS+P_POST_AUDIT`, `P_FOCUS+P_POST_AUDIT+P_SUBMIT_VETO`)\n on 36 distinct safe_s1 fit calls (12 pre + 12 post_work + 12 pre_sub; zero outcome labels).\n3. Fits 3 4-fold out-of-task CV non-negative quadratic GeGLU gates (`thought_quad`, `post_thought`, `submit_veto`)\n and saves `code/data/t12_tri_stats.pt` for Entry 1 (`tri-phase-concise-audit-veto`, r=3, 180 matrices).\n[... 308 lines cut ...]\n T12_PROBES.mkdir(parents=True, exist_ok=True)\n dst = T12_PROBES / \"held26_submit_calls.jsonl\"\n\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2jssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_phase_a_g31.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/64/output.txt"},{"i":65,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n4C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_pts.py\nimport pathlib, torch\nd = pathlib.Path(\"/home/keith/gemma-v2/wsp31/authors/gemini/code/data\")\nfor fn in sorted(d.glob(\"*.pt\")):\n obj = torch.load(fn, map_location=\"cpu\", weights_only=False)\n print(\"===\", fn.name, \"===\")\n if isinstance(obj, dict):\n for k, v in obj.items():\n if hasattr(v, \"shape\"):\n print(f\" {k}: Tensor{tuple(v.shape)} {v.dtype}\")\n elif isinstance(v, dict):\n[line removed by the dashboard scrubber]\n elif isinstance(v, list):\n print(f\" {k}: list(len={len(v)})\")\n else:\n print(f\" {k}: {type(v).__name__}={str(v)[:100]}\")\n[Created At: 2026-11-14T15:06:13-05:00\nCompleted At: 2026-11-14T15:06:18-05:00\nCreated file.\n[... 14 lines cut ...]\n[line removed by the dashboard scrubber]\n)\n% elif isinstance(v, list):\n7\n3 print(f\" {k}: list(len={len(v)})\")\nF\nB print(f\" {k}: {type(v).__name__}={str(v)[:100]}\")\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/65/output.txt"},{"i":66,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\inspect_pts.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect all .pt files in code/data\"}2\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_pts.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py'\nCreated At: 2026-11-14T15:06:14-05:00\nCompleted At: 2026-11-14T15:06:22-05:00\nCommand exited with code 0.\n\nCommand output:\n=== gemini_directions.pt ===\n f1_dirs: dict(['0.o_proj', '1.o_proj', '2.o_proj', '3.o_proj', '4.o_proj', '5.o_proj', '6.o_proj', '7.o_proj', '8.o_proj', '9.o_proj', '10.o_proj', '11.o_proj'])\n f2_dirs: dict(['20.attn_raw', '21.attn_raw', '22.attn_raw', '23.attn_raw', '24.attn_raw', '25.attn_raw', '26.attn_raw', '27.attn_raw', '28.attn_raw', '29.attn_raw', '30.attn_raw', '31.attn_raw'])\n f3_neurons: dict([30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 57, 58])\n summary: dict(['fit_tasks', 'check_tasks', 'f1_heldout_auc', 'f2_heldout_auc', 'f3_heldout_summary', 'f3_per_layer'])\n=== gemini_t5_directions.pt ===\n f_close: dict(['10.o_proj', '11.o_proj', '12.o_proj', '13.o_proj', '14.o_proj', '15.o_proj', '16.o_proj', '17.o_proj', '18.o_proj', '19.o_proj', '20.o_proj', '21.o_proj'])\n f_damp: dict(['24.attn_raw', '25.attn_raw', '26.attn_raw', '27.attn_raw', '28.attn_raw', '29.attn_raw', '30.attn_raw', '31.attn_raw', '32.attn_raw', '33.attn_raw', '34.attn_raw', '35.attn_raw'])\n quiet_pair: dict([24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35])\n commit_neurons: dict([32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43])\n colon_neurons: dict([48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59])\n summary: dict(['captured_calls_count', 'fit_tasks_count', 'check_tasks_count', 'fit_task_ids', 'check_task_ids', 'nullspace_close_r4', 'ortho_damp_r2', 'commit_gate', 'colon_guard'])\n=== t12_mk_stats.pt ===\n[... 72 lines cut ...]\n fit_calls: list(len=32)\n held_calls: list(len=14)\n p_audit: str=Before editing or calling submit_patch, re-read every requirement and example in the Problem Stateme\n p_pre: str=While exploring before your first edit, locate the target file and run one minimal reproduction comm\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_pts.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_pts.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/66/output.txt"},{"i":67,"kind":"raw","long":false,"text":":(bot-9095eb82-e884-4b80-ae4a-853566667a7eB!\n\tsessionID\nInvestigating the scripts `t12_fast_finish.py` and `t12_sprint_finalize.py` to understand the construction of the data files used in the analysis of `0055` and `0056`. Simultaneously, `task-48` is processing JSON traces from 7 batches; its completion will provide further data for the investigation.\n\n\n2(bot-9095eb82-e884-4b80-ae4a-853566667a7e:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 150 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_fast_finish.py on wrx90\"}:"},{"i":68,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 150 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_fast_finish.py on wrx90\"}:\njssh -o BatchMode=yes wrx90 'head -n 150 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py'\n_\n-Created At: 2026-11-14T15:06:29-05:00\nCompleted At: 2026-11-14T15:06:32-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Fast GPU-0 completion (`~3.5 min` total):\n1. Reuses ALREADY-SAVED `code/data/t12_tri_stats.pt` (36 fit calls, 3 OOF gates, 3 split-half shifts).\n[line removed by the dashboard scrubber]\n on 20 stratified distinct `safe_s1` fit calls (5 per fold x 4 folds, max_tok <= 6400) using single-QR\n OOF-shrunk dual ridge (`~130s`), saving `code/data/t12_mk_stats.pt`.\n3. Evaluates `e1_tri_m/s` and `e2_mk_m/s` + matched controls on 15 unseen `safe_s1` held-out calls + 8 `closeprobe`\n records (`~65s`), saving `scratch/t12_phase_a_report.json`.\n\"\"\"\nimport gc, json, math, os, pathlib, sys, time\nos.environ[\"G31_ATT_BUDGET\"] = \"4.0e8\"\n\n[... 289 lines cut ...]\n st_tri = torch.load(tri_stats_path, map_location=\"cpu\", weights_only=False)\n gates_dict = st_tri[\"gates\"]\n fit_meta_all = st_tri[\"fit_calls\"]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2jssh -o BatchMode=yes wrx90 'head -n 150 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/68/output.txt"},{"i":69,"kind":"raw","long":false,"text":":(bot-2878491d-2413-4af6-8082-5fbcd2c8983bB!\n\tsessionID\n2(bot-2878491d-2413-4af6-8082-5fbcd2c8983b:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"151,290p\\\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read rest of t12_fast_finish.py\"}:"},{"i":70,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"151,290p\\\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read rest of t12_fast_finish.py\"}:\npssh -o BatchMode=yes wrx90 'sed -n \"151,290p\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py'\n}\n 6 per fold x 4 folds!)\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[... 267 lines cut ...]\n ao_in_g = ao_in_cpu[ci].to(\"cuda:0\")\n o_raw_ed = o_raw_cpu[ci].to(\"cuda:0\") + F.linear(F.linear(ao_in_g.to(BF), A_o_bf), B_o_bf)\n h_ed_cpu[ci] = (model.rms(o_raw_ed, d_l[\"post_attention_layernorm\"]) + h_prev).cpu()\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2pssh -o BatchMode=yes wrx90 'sed -n \"151,290p\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_fast_finish.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/70/output.txt"},{"i":71,"kind":"raw","long":false,"text":":(bot-c1f8631f-b2ea-4bbc-a7c5-8bca3a873646B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\nThe script's structure directly addresses the efficiency bottleneck by dequantizing matrices only once within a loop that processes multiple calls. This approach yields significant performance gains on the CPU. The `P_FOCUS` directive, present in the problematic runs, seems to be a causal factor. Examining the text of `P_FOCUS` is crucial for understanding the performance discrepancies.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-c1f8631f-b2ea-4bbc-a7c5-8bca3a873646:\n{\"EndLine\":380,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\",\"StartLine\":115}:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_hold1.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t9_hold1.py on wrx90\"}Z"},{"i":72,"kind":"raw","long":true,"text":"{\"EndLine\":380,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\",\"StartLine\":115}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\n^\n[Created At: 2026-11-14T15:06:55-05:00\nCompleted At: 2026-11-14T15:06:56-05:00\nShowing lines 115-380 of 555\n115: \n116: ab = max(float(abar[l].item()), 0.90)\n117: sig = max(float(rmsy[l].item()), 1e-6)\n118: \n119: d_raw = (sig / ab) * (inv_w * g_want)\n120: raw_norm = float(d_raw.norm().item())\n121: eta_lin = (ab * raw_norm) / (sqrtD * sig)\n122: \n123: if eta_lin <= 1e-9:\n124: u_fb = inv_w * (delta if float(delta.norm()) > 1e-12 else torch.ones(D, dtype=torch.float64))\n125: u_fb = u_fb / max(float(u_fb.norm()), 1e-12)\n126: d_col = u_fb * (min_rel_floor * float(fnorms[f\"{l}.down_proj\"]))\n127: elif eta_lin >= eta_max:\n128: d_col = d_raw * (eta_max / eta_lin)\n[... 247 lines cut ...]\n376: \"dose_scale\": dose_scale,\n377: \"max_mat_rel\": max_mat_rel,\n378: \"target_net_rel\": target_net_rel,\n379: \"n_matrices\": len(svd_items),\n380: })\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt s("},{"i":73,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_hold1.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t9_hold1.py on wrx90\"}2\ncssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_hold1.py'\nl\n4Created At: 2026-11-14T15:06:56-05:00\nCompleted At: 2026-11-14T15:06:58-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Turn 9 GPU Hold 1 (author: gemini):\n1. Captures exact base + prompted (P_audit, P_pre) forward-pass summary stats on 32 safe_s1 fit calls\n (16 pre_edit + 16 post_edit across 32 distinct fit tasks; zero Stage-2 overlap, zero outcome labels).\n2. Fits 4-fold out-of-fold cross-validated ridge gates (thought_quad, comp_thought_quad, pre_thought, post_thought)\n and incremental reliability-shrunk stream shifts; saves compact CPU-rebuildable `code/data/t9_stats.pt`.\n3. Builds candidate Entry 1 (spec-audit-thought-gate) and Entry 2 (dual-phase-action-audit / dual-audit-boost)\n edit + matched control pairs via `t9_build.py` and evaluates them on 14 unseen safe_s1 held-out calls\n (7 pre_edit + 7 post_edit).\n\"\"\"\nimport json\nimport math\n[... 307 lines cut ...]\n sel_h_post = [dict(h_post[k], phase=\"post\") for k in (hpo_distinct + hpo_overlap)[:7]]\n\n return sel_f_pre + sel_f_post, sel_h_pre + sel_h_post\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2cssh -o BatchMode=yes wrx90 'head -n 160 /home/keith/gemma-v2/wsp31/authors/gemini/code/t9_hold1.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/73/output.txt"},{"i":74,"kind":"raw","long":false,"text":":(bot-f8be05b1-b195-4490-9a98-36eddeae4e14B!\n\tsessionID\n`cap_dual_t9` is in the build script and it looks like a third recipe is there. This suggests that the script handles more than the initially expected two recipes. Examining the build script clarifies what the complete set of recipes is.\n\n\n2(bot-f8be05b1-b195-4490-9a98-36eddeae4e14:\n{\"EndLine\":470,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\",\"StartLine\":381}:"},{"i":75,"kind":"raw","long":true,"text":"{\"EndLine\":470,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\",\"StartLine\":381}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\n%\n\"Created At: 2026-11-14T15:07:21-05:00\nCompleted At: 2026-11-14T15:07:21-05:00\nShowing lines 381-470 of 555\n381: elif recipe == \"cap_dual_t9\":\n382: quiet_idx = st[\"quiet_idx\"]\n383: g0_name = \"pre_thought\" if dose_veto < 0 else \"thought_quad\"\n384: sh0_name = \"pre_only\" if \"pre_only\" in st[\"shifts\"] else \"audit_all\"\n385: g0 = st[\"gates\"][g0_name]\n386: g1 = st[\"gates\"][\"post_thought\"]\n387: sh0 = st[\"shifts\"][sh0_name]\n388: sh1 = st[\"shifts\"][\"audit_post\"]\n389: \n390: cols0, wants0, rhos0, etas0 = solve_stream_columns_cap(\n391: e_edit, layers, sh0, g0, dose=dose_focus, gamma=gamma, eta_max=eta_max,\n392: max_col_rel=max_col_rel, is_phase_gate=(g0_name != \"thought_quad\")\n393: )\n394: cols1, wants1, rhos1, etas1 = solve_stream_columns_cap(\n[... 71 lines cut ...]\n466: \"shifts\": {\"focus_all\": sh_mock, \"audit_post\": sh_mock, \"veto_submit\": sh_mock},\n467: }\n468: p_tri = td_p / \"tri.pt\"\n469: torch.save(st_tri, p_tri)\n470: _, _, re1, rc1, _ = build_pair(\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/60/output.txt"},{"i":76,"kind":"raw","long":true,"text":"R[Message] timestamp=2026-11-14T20:06:59Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-48\" finished with result:\nThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCommand exited with code 0.\n\nCommand output:\nsafe_v2=120, valid119=119\nx003/base | N=119 SOLV=81 WC=24 CUT= 6 EMP= 8 | toks= 7461 th~=5317 calls=21.0(pre=9.0,post=10.0) read= 8.8 run=14.7 edit=2.34(fail=0.90) noTC=223 testAfter=104 u52=1.00%\nx003/aa | N=119 SOLV=82 WC=22 CUT= 9 EMP= 6 | toks= 7338 th~=5550 calls=23.0(pre=9.0,post=9.0) read= 8.2 run=15.2 edit=2.51(fail=1.03) noTC=215 testAfter=108 u52=0.75%\nx003/e0035 | N=119 SOLV=79 WC=27 CUT= 8 EMP= 5 | toks= 8424 th~=5736 calls=20.0(pre=9.0,post=9.0) read= 8.2 run=14.5 edit=2.45(fail=0.79) noTC=222 testAfter=110 u52=0.81%\nx003/e0036 | N=119 SOLV=78 WC=20 CUT=15 EMP= 6 | toks= 8011 th~=5570 calls=24.0(pre=10.0,post=10.0) read= 9.7 run=15.7 edit=2.19(fail=0.82) noTC=227 testAfter=107 u52=1.07%\n-------------------------------------------------------------------------------------------------------------------------------------------------\nx004/base | N=119 SOLV=78 WC=27 CUT= 8 EMP= 6 | toks= 8231 th~=5213 calls=22.0(pre=9.0,post=9.0) read= 8.1 run=15.3 edit=2.24(fail=0.77) noTC=236 testAfter=110 u52=0.54%\nx004/aa | N=119 SOLV=76 WC=28 CUT= 8 EMP= 7 | toks= 7915 th~=5313 calls=21.0(pre=9.0,post=10.0) read= 8.1 run=15.1 edit=2.29(fail=0.86) noTC=227 testAfter=109 u52=0.76%\nx004/e0038 | N=119 SOLV=75 WC=33 CUT= 6 EMP= 5 | toks= 6279 th~=4117 calls=19.0(pre=9.0,post=9.0) read= 7.5 run=14.2 edit=2.34(fail=0.76) noTC=240 testAfter=111 u52=0.64%\nx004/e0039 | N=119 SOLV=79 WC=27 CUT=10 EMP= 3 | toks= 6027 th~=3633 calls=19.0(pre=9.0,post=9.0) read= 7.4 run=13.9 edit=2.32(fail=0.63) noTC=226 testAfter=112 u52=0.27%\n-------------------------------------------------------------------------------------------------------------------------------------------------\nx005/base | N=119 SOLV=75 WC=27 CUT= 8 EMP= 9 | toks= 8793 th~=5694 calls=24.0(pre=10.0,post=11.0) read= 9.4 run=16.3 edit=2.44(fail=0.91) noTC=227 testAfter=107 u52=1.01%\nx005/aa | N=119 SOLV=73 WC=24 CUT=16 EMP= 6 | toks= 8864 th~=6014 calls=24.0(pre=10.0,post=10.0) read= 8.9 run=15.5 edit=3.06(fail=1.61) noTC=226 testAfter=106 u52=1.15%\n[... 274 lines cut ...]\nBucket | N | uned_mean | x006/e0043 | x006/e0044 | b010/e0048 | x008/e0050 | x009/e0055 | x009/e0056\n0% (0/14) | 25 | 0.00 | 0/25 | 2/25 | 1/25 | 0/25 | 0/25 | 0/25 \n1-25% | 7 | 0.79 | 0/7 | 1/7 | 1/7 | 2/7 | 3/7 | 0/7 \n25-60% | 11 | 4.43 | 5/11 | 6/11 | 6/11 | 4/11 | 3/11 | 7/11 \n60-85% | 8 | 5.71 | 6/8 | 6/8 | 7/8 | 7/8 | 7/8 | 7/8 \n85-100% | 68 | 66.93 | 68/68 | 67/68 | 66/68 | 68/68 | 65/68 | 66/68 \n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-48.log"},{"i":77,"kind":"raw","long":false,"text":":(bot-f10c5ae7-cdad-41dc-b324-e67b5b6c4621B!\n\tsessionID\n2(bot-f10c5ae7-cdad-41dc-b324-e67b5b6c4621:\n{\"EndLine\":105,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt\",\"StartLine\":25}:"},{"i":78,"kind":"raw","long":true,"text":"{\"EndLine\":105,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt\",\"StartLine\":25}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt\nN\nLCreated At: 2026-11-14T15:07:29-05:00\nCompleted At: 2026-11-14T15:07:30-05:00\nShowing lines 25-105 of 120\n25: b010/aa | N=119 SOLV=75 WC=28 CUT=12 EMP= 4 | toks= 8060 th~=5197 calls=22.0(pre=11.0,post=10.0) read= 8.7 run=15.3 edit=2.45(fail=1.02) noTC=228 testAfter=108 u52=0.68%\n26: b010/e0047 | N=119 SOLV=75 WC=22 CUT=17 EMP= 5 | toks= 8373 th~=5392 calls=20.0(pre=10.0,post=9.0) read= 8.6 run=14.6 edit=2.50(fail=1.08) noTC=222 testAfter=112 u52=1.61%\n27: b010/e0048 | N=119 SOLV=81 WC=22 CUT=12 EMP= 4 | toks= 7535 th~=5386 calls=20.0(pre=9.0,post=10.0) read= 8.2 run=14.7 edit=2.50(fail=1.07) noTC=217 testAfter=113 u52=1.46%\n28: -------------------------------------------------------------------------------------------------------------------------------------------------\n29: x008/base | N=119 SOLV=76 WC=27 CUT=11 EMP= 5 | toks= 8442 th~=5684 calls=23.0(pre=10.0,post=10.0) read= 8.9 run=15.7 edit=2.91(fail=1.32) noTC=231 testAfter=108 u52=0.92%\n30: x008/aa | N=119 SOLV=78 WC=23 CUT=12 EMP= 6 | toks= 7156 th~=5160 calls=21.0(pre=10.0,post=9.0) read= 8.6 run=15.3 edit=2.50(fail=0.85) noTC=231 testAfter=108 u52=1.04%\n31: x008/e0049 | N=119 SOLV=78 WC=29 CUT= 8 EMP= 4 | toks= 5720 th~=3912 calls=18.0(pre=9.0,post=8.0) read= 7.5 run=13.7 edit=2.58(fail=1.05) noTC=242 testAfter=108 u52=1.05%\n32: x008/e0050 | N=119 SOLV=81 WC=26 CUT=10 EMP= 2 | toks= 5952 th~=3752 calls=21.0(pre=9.0,post=10.0) read= 7.6 run=14.7 edit=2.70(fail=1.01) noTC=246 testAfter=112 u52=0.62%\n33: -------------------------------------------------------------------------------------------------------------------------------------------------\n34: x009/base | N=119 SOLV=83 WC=25 CUT= 8 EMP= 3 | toks= 8296 th~=5941 calls=22.0(pre=10.0,post=10.0) read= 8.5 run=15.8 edit=2.21(fail=0.82) noTC=224 testAfter=111 u52=0.71%\n35: x009/aa | N=119 SOLV=80 WC=21 CUT= 8 EMP=10 | toks= 8323 th~=5534 calls=21.0(pre=10.0,post=9.0) read= 8.7 run=15.0 edit=2.05(fail=0.81) noTC=215 testAfter=108 u52=1.01%\n36: x009/e0055 | N=119 SOLV=78 WC=39 CUT= 2 EMP= 0 | toks= 3427 th~=1968 calls=11.0(pre=5.0,post=6.0) read= 3.6 run= 7.8 edit=2.42(fail=0.85) noTC=242 testAfter=113 u52=0.74%\n37: x009/e0056 | N=119 SOLV=80 WC=24 CUT=12 EMP= 3 | toks= 6483 th~=4456 calls=16.0(pre=8.0,post=7.0) read= 6.3 run=11.9 edit=2.39(fail=0.82) noTC=222 testAfter=110 u52=1.14%\n38: -------------------------------------------------------------------------------------------------------------------------------------------------\n[... 62 lines cut ...]\n101: e0056: WRONG_CLEAN calls=24(pre= 3,post=21,read= 5,run=15,edit= 4) toks=13553 th_c= 0 testAfter=True fail_t=1\n102: [LOSS] [task]:\n103: base : SOLVED calls=34(pre=14,post=20,read=14,run=17,edit= 3) toks=11416 th_c= 0 testAfter=False fail_t=0\n104: aa : SOLVED calls=14(pre= 9,post= 5,read= 6,run= 6,edit= 2) toks=11137 th_c= 0 testAfter=True fail_t=0\n105: e0055: WRONG_CLEAN calls= 8(pre= 4,post= 4,read= 3,run= 4,edit= 1) toks= 2045 th_c= 0 testAfter=True fail_t=1\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/48/output.txt"},{"i":79,"kind":"raw","long":true,"text":":(bot-24b89090-1f2e-4999-b996-f63f70f739e8B!\n\tsessionID\nInitial autopsy reveals a highly focused mechanistic explanation within the Python script's lines 34-37. This section warrants immediate, detailed analysis due to its perceived clarity and potential significance in understanding the overall program logic. Further scrutiny is required to determine the exact nature and implications of this observed mechanism.\n\n\nObserved that x009 instances show full request logs, particularly `e0055` and `e0056` which exhibit clean syntax. Focusing on potential relationships between the syntactic cleanliness and the availability of logs, further investigation will focus on these two instances. The presence of complete logs and clean syntax in specific instances suggests a correlation that needs to be understood.\n\n\n[line removed by the dashboard scrubber]\n\n\n[line removed by the dashboard scrubber]\n\n\n[line removed by the dashboard scrubber]\n\n\n[line removed by the dashboard scrubber]\n\n\nThe analysis of the `t12_phase_a_g31.py` script reveals a significant issue: the `audit_post` calculation is heavily influenced by the `P_FOCUS` prompt. This contamination results in a much lower cosine similarity value, effectively diminishing the influence of `audit_post` and shrinking the critical `j_1` value in `e0056` nearly to zero. Furthermore, `e0056` fails to reduce cutoffs.\n\nInvestigating further, I'll examine the positive outcomes across all program arms (`e0044`, `e0050`, `e0048`, `e0043`, `e0039`) at the deep trace level. I will use a CPU-based diagnostic script to analyze the exact failure modes of the 51 tasks where `uned_rate < 0.85` across 14 unedited runs.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-24b89090-1f2e-4999-b996-f63f70f739e8:u\n){\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Deep Stage-2-safe comparison of x2 failures across 14 unedited runs + e0044, e0050, e0048, e0055, e0056.\\\"\\\"\\\"\\nimport json\\nimport pathlib\\nimport statistics\\nfrom collections import Counter\\n\\nfrom forensic_t15_x009 import load_safe_sets, analyze_arm\\n\\nR = pathlib.Path(\\\"/home/keith/gemma-v2\\\")\\nBATCHES = R / \\\"results/wsp31/batches\\\"\\n\\n\\ndef main():\\n _, safe_v2, valid119 = load_safe_sets()\\n\\n batches = {\\n \\\"x003\\\": [\\\"base\\\", \\\"aa\\\"],\\n \\\"x004\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0038\\\", \\\"e0039\\\"],\\n \\\"x005\\\": [\\\"base\\\", \\\"aa\\\"],\\n \\\"x006\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0043\\\", \\\"e0044\\\"],\\n \\\"b010\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0047\\\", \\\"e0048\\\"],\\n \\\"x008\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0049\\\", \\\"e0050\\\"],\\n \\\"x009\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0055\\\", \\\"e0056\\\"],\\n }\\n data = {b: {a: analyze_arm(BATCHES / b / a, valid119) for a in arms} for b, arms in batches.items()}\\n\\n uned = [(f\\\"{b}/{a}\\\", data[b][a]) for b in batches for a in (\\\"base\\\", \\\"aa\\\")]\\n\\n # Total failure breakdown across all 14 * 119 = 1666 unedited episodes\\n cats_all = Counter()\\n wc_toks, wc_calls, wc_reads, wc_edits, wc_ft = [], [], [], [], []\\n cut_toks, cut_calls, cut_aerr = [], [], Counter()\\n for _, st in uned:\\n for iid, v in st.items():\\n cats_all[v[\\\"cat\\\"]] += 1\\n if v[\\\"cat\\\"] == \\\"WRONG_CLEAN\\\":\\n wc_toks.append(v[\\\"out_toks\\\"])\\n wc_calls.append(v[\\\"n_calls\\\"])\\n wc_reads.append(v[\\\"n_read_calls\\\"])\\n wc_edits.append(v[\\\"n_edit_calls\\\"])\\n wc_ft.append(v[\\\"failed_tests\\\"])\\n elif v[\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\"):\\n cut_toks.append(v[\\\"out_toks\\\"])\\n cut_calls.append(v[\\\"n_calls\\\"])\\n cut_aerr[v[\\\"aerr\\\"]] += 1\\n\\n tot_ep = sum(cats_all.values())\\n tot_fail = tot_ep - cats_all[\\\"SOLVED\\\"]\\n print(f\\\"=== 14 Unedited x2 Runs ({tot_ep} episodes on 119 Stage-2-disjoint tasks) ===\\\")\\n print(f\\\" SOLVED: {cats_all['SOLVED']} ({100*cats_all['SOLVED']/tot_ep:.1f}% -\\u003e {cats_all['SOLVED']/14:.2f}/119 per run)\\\")\\n for k in [\\\"WRONG_CLEAN\\\", \\\"CU\n[... 3446 characters cut ...]"},{"i":80,"kind":"raw","long":true,"text":"){\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Deep Stage-2-safe comparison of x2 failures across 14 unedited runs + e0044, e0050, e0048, e0055, e0056.\\\"\\\"\\\"\\nimport json\\nimport pathlib\\nimport statistics\\nfrom collections import Counter\\n\\nfrom forensic_t15_x009 import load_safe_sets, analyze_arm\\n\\nR = pathlib.Path(\\\"/home/keith/gemma-v2\\\")\\nBATCHES = R / \\\"results/wsp31/batches\\\"\\n\\n\\ndef main():\\n _, safe_v2, valid119 = load_safe_sets()\\n\\n batches = {\\n \\\"x003\\\": [\\\"base\\\", \\\"aa\\\"],\\n \\\"x004\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0038\\\", \\\"e0039\\\"],\\n \\\"x005\\\": [\\\"base\\\", \\\"aa\\\"],\\n \\\"x006\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0043\\\", \\\"e0044\\\"],\\n \\\"b010\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0047\\\", \\\"e0048\\\"],\\n \\\"x008\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0049\\\", \\\"e0050\\\"],\\n \\\"x009\\\": [\\\"base\\\", \\\"aa\\\", \\\"e0055\\\", \\\"e0056\\\"],\\n }\\n data = {b: {a: analyze_arm(BATCHES / b / a, valid119) for a in arms} for b, arms in batches.items()}\\n\\n uned = [(f\\\"{b}/{a}\\\", data[b][a]) for b in batches for a in (\\\"base\\\", \\\"aa\\\")]\\n\\n # Total failure breakdown across all 14 * 119 = 1666 unedited episodes\\n cats_all = Counter()\\n wc_toks, wc_calls, wc_reads, wc_edits, wc_ft = [], [], [], [], []\\n cut_toks, cut_calls, cut_aerr = [], [], Counter()\\n for _, st in uned:\\n for iid, v in st.items():\\n cats_all[v[\\\"cat\\\"]] += 1\\n if v[\\\"cat\\\"] == \\\"WRONG_CLEAN\\\":\\n wc_toks.append(v[\\\"out_toks\\\"])\\n wc_calls.append(v[\\\"n_calls\\\"])\\n wc_reads.append(v[\\\"n_read_calls\\\"])\\n wc_edits.append(v[\\\"n_edit_calls\\\"])\\n wc_ft.append(v[\\\"failed_tests\\\"])\\n elif v[\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\"):\\n cut_toks.append(v[\\\"out_toks\\\"])\\n cut_calls.append(v[\\\"n_calls\\\"])\\n cut_aerr[v[\\\"aerr\\\"]] += 1\\n\\n tot_ep = sum(cats_all.values())\\n tot_fail = tot_ep - cats_all[\\\"SOLVED\\\"]\\n print(f\\\"=== 14 Unedited x2 Runs ({tot_ep} episodes on 119 Stage-2-disjoint tasks) ===\\\")\\n print(f\\\" SOLVED: {cats_all['SOLVED']} ({100*cats_all['SOLVED']/tot_ep:.1f}% -\\u003e {cats_all['SOLVED']/14:.2f}/119 per run)\\\")\\n for k in [\\\"WRONG_CLEAN\\\", \\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\", \\\"EMPTY_FINISHED\\\"]:\\n print(f\\\" {k:15s}: {cats_all[k]:4d} ({100*cats_all[k]/tot_fail:5.1f}% of failures, {cats_all[k]/14:.2f}/run)\\\")\\n print(f\\\" WRONG_CLEAN medians: toks={statistics.median(wc_toks):.0f}, calls={statistics.median(wc_calls):.1f}, reads={statistics.median(wc_reads):.1f}, edits={statistics.median(wc_edits):.1f}, failed_tests={statistics.median(wc_ft):.1f}\\\")\\n print(f\\\" CUTOFF/EMPTY_LIM medians: toks={statistics.median(cut_toks):.0f}, calls={statistics.median(cut_calls):.1f}, aerr={dict(cut_aerr)}\\\")\\n\\n # Per-task table for all tasks with 0 \\u003c uned_rate \\u003c 0.85 OR solved by any edit when uned_rate == 0\\n print(\\\"\\\\n=== Tasks with 0 \\u003c uned_rate \\u003c= 0.85 OR solved by an edit at 0/14 ===\\\")\\n rows = []\\n for iid in sorted(valid119):\\n u_sol = sum(1 for _, st in uned if st[iid][\\\"resolved\\\"])\\n u_wc = sum(1 for _, st in uned if st[iid][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\")\\n u_cut = sum(1 for _, st in uned if st[iid][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\"))\\n e43 = int(data[\\\"x006\\\"][\\\"e0043\\\"][iid][\\\"resolved\\\"])\\n e44 = int(data[\\\"x006\\\"][\\\"e0044\\\"][iid][\\\"resolved\\\"])\\n e48 = int(data[\\\"b010\\\"][\\\"e0048\\\"][iid][\\\"resolved\\\"])\\n e50 = int(data[\\\"x008\\\"][\\\"e0050\\\"][iid][\\\"resolved\\\"])\\n e55 = int(data[\\\"x009\\\"][\\\"e0055\\\"][iid][\\\"resolved\\\"])\\n e56 = int(data[\\\"x009\\\"][\\\"e0056\\\"][iid][\\\"resolved\\\"])\\n if (0 \\u003c u_sol \\u003c= 11) or (u_sol == 0 and (e43 or e44 or e48 or e50 or e55 or e56)):\\n rows.append((u_sol, iid, u_wc, u_cut, e43, e44, e48, e50, e55, e56))\\n rows.sort()\\n print(f\\\"{'Task':56s} | uSol | uWC | uCut | 43 44 48 50 55 56\\\")\\n for u_sol, i\n[... 2251 characters cut ...]"},{"i":81,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\deep_compare_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run deep_compare_t15.py on wrx90\"}2\n,4fbddbc5-e478-44c0-a42f-2366c93d8394/task-81\n}file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-81.log\"\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\deep_compare_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py': Run deep_compare_t15.py on wrx90B\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\deep_compare_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py'\nI\n!Command exited with code 0.\n\nCommand output:\n=== 14 Unedited x2 Runs (1666 episodes on 119 Stage-2-disjoint tasks) ===\n SOLVED: 1090 (65.4% -> 77.86/119 per run)\n WRONG_CLEAN : 348 ( 60.4% of failures, 24.86/run)\n CUTOFF_DIFF : 144 ( 25.0% of failures, 10.29/run)\n EMPTY_LIMIT : 73 ( 12.7% of failures, 5.21/run)\n EMPTY_FINISHED : 11 ( 1.9% of failures, 0.79/run)\n WRONG_CLEAN medians: toks=9089, calls=23.0, reads=7.0, edits=2.0, failed_tests=1.0\n CUTOFF/EMPTY_LIM medians: toks=16759, calls=35.0, aerr={'Agent exceeded session timeout (7.5 min)': 216, 'Agent exceeded turns budget (80 turns)': 1}\n\n=== Tasks with 0 < uned_rate <= 0.85 OR solved by an edit at 0/14 ===\nTask | uSol | uWC | uCut | 43 44 48 50 55 56\n[... 88 lines cut ...]\n [task] (13/14) -> 48:CUTO\n [task] (13/14) -> 55:WRON\n[line removed by the dashboard scrubber]\n [task] (14/14) -> 44:CUTO\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\deep_compare_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_compare_t15.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/81/output.txt"},{"i":82,"kind":"raw","long":false,"text":":(bot-9ac3a2a8-342f-4b78-bf3d-262455888b40B!\n\tsessionID\nThe task `deep_compare_t15.py` is running, so looking at other relevant tasks (`t12_sprint_finalize.py`, `instant_package_now.py`) and a potential report file on `wrx90` to gather pre-test numbers from `0055` and `0056`. This information will help understand the testing context.\n\n\n2(bot-9ac3a2a8-342f-4b78-bf3d-262455888b40:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12* /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t9*; head -n 100 /home/keith/gemma-v2/wsp31/authors/gemini/code/instant_package_now.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect Turn 12 and Turn 9 pre-test reports\"}:"},{"i":83,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12* /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t9*; head -n 100 /home/keith/gemma-v2/wsp31/authors/gemini/code/instant_package_now.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect Turn 12 and Turn 9 pre-test reports\"}:\n+Inspect Turn 12 and Turn 9 pre-test reports\nssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12* /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t9*; head -n 100 /home/keith/gemma-v2/wsp31/authors/gemini/code/instant_package_now.py'\nOCreated At: 2026-11-14T15:08:54-05:00\nCompleted At: 2026-11-14T15:08:56-05:00\nCommand exited with code 0.\n\nCommand output:\n-rw-rw-r-- 1 keith keith 51 Nov 14 12:28 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_cpu_ins.log\n-rw-rw-r-- 1 keith keith 8 Nov 14 12:28 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_cpu_ins.pid\n-rw-rw-r-- 1 keith keith 744 Nov 14 12:49 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_fast_finish.log\n-rw-rw-r-- 1 keith keith 8 Nov 14 12:43 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_fast_finish.pid\n-rw-rw-r-- 1 keith keith 8 Nov 14 12:06 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_flock.pid\n-rw-rw-r-- 1 keith keith 564 Nov 14 12:41 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_followup.log\n-rw-rw-r-- 1 keith keith 8 Nov 14 12:35 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_followup.pid\n-rw-rw-r-- 1 keith keith 1886 Nov 14 12:40 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_gpu.log\n[line removed by the dashboard scrubber]\n-rw-rw-r-- 1 keith keith 65907 Nov 14 13:01 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_size_tri-phase-concise-audit-veto.json\n-rw-rw-r-- 1 keith keith 2734 Nov 14 08:41 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t9_fp_e1_d12_edit.json\n-rw-rw-r-- 1 keith keith 2736 Nov 14 08:42 /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t9_fp_e1_d16_edit.json\n[... 253 lines cut ...]\n[line removed by the dashboard scrubber]\n_, info2 = package_t12.build_and_verify_adapters(slug2, cfg_e2)\nse2, sc2 = info2[\"size_edit\"], info2[\"size_ctrl\"]\nassert se2[\"net_rel\"] >= 0.003 and se2[\"changed\"] >= 100\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12* /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t9*; head -n 100 /home/keith/gemma-v2/wsp31/authors/gemini/code/instant_package_now.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/83/output.txt"},{"i":84,"kind":"raw","long":false,"text":":(bot-bd7059b8-7ee2-4f66-ad65-cb525dd2e268B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\n2(bot-bd7059b8-7ee2-4f66-ad65-cb525dd2e268:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_fast_finish.log; echo \\\"=== followup ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_followup.log'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_fast_finish.log and t12_followup.log\"}:"},{"i":85,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_fast_finish.log; echo \\\"=== followup ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_followup.log'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_fast_finish.log and t12_followup.log\"}:\n-Read t12_fast_finish.log and t12_followup.log\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_fast_finish.log; echo \"=== followup ===\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_followup.log'\nCreated At: 2026-11-14T15:09:08-05:00\nCompleted At: 2026-11-14T15:09:10-05:00\nCommand exited with code 0.\n\nCommand output:\n[12:43:58] Starting t12_fast_finish.py (mk compile + unseen held-out + closeprobe)...\n[line removed by the dashboard scrubber]\n[95.2s] Captured 24 phase-matched teacher targets (cached=396)\n[line removed by the dashboard scrubber]\n [114.6s L05 GLOB] o: beta=0.460 r2=0.128 rel=0.15% | d: beta=0.032 r2=0.002 rel=0.01%\n [164.0s L11 GLOB] o: beta=0.425 r2=0.088 rel=0.07% | d: beta=0.307 r2=0.034 rel=0.04%\n [213.3s L17 GLOB] o: beta=0.375 r2=0.070 rel=0.06% | d: beta=0.178 r2=0.014 rel=0.03%\n [262.5s L23 GLOB] o: beta=0.349 r2=0.065 rel=0.06% | d: beta=0.108 r2=0.013 rel=0.04%\n [360.8s L35 GLOB] o: beta=0.210 r2=0.009 rel=0.02% | d: beta=0.120 r2=0.004 rel=0.03%\n=== followup ===\n[12:35:01] Queued followup safeguard on gpu0.lock...\n[12:41:11] Followup: Running t12_step4_only.py using saved .pt stats...\n[... 28 lines cut ...]\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t12_step4_only.py\", line 35, in main\n assert tri_stats_path.exists() and mk_stats_path.exists(), \"Missing saved .pt stats!\"\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nAssertionError: Missing saved .pt stats!\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_fast_finish.log; echo \"=== followup ===\"; cat /home/keith/gemma-v2/wsp31/authors/gemini/scratch/t12_followup.log':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/85/output.txt"},{"i":86,"kind":"raw","long":false,"text":":(bot-8c81abc7-b94c-4ee5-9362-bd3debf909a2B!\n\tsessionID\nReading the script that generated the final stats file to understand the exact generation process at the specified time. This should clarify how the intermediate data was finalized. The concurrent task's completion time is being tracked to understand the overall process dependencies.\n\n\n2(bot-8c81abc7-b94c-4ee5-9362-bd3debf909a2:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_final_gpu_90s.py on wrx90\"}:"},{"i":87,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_final_gpu_90s.py on wrx90\"}:\nlssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py'\nV\n)Created At: 2026-11-14T15:09:19-05:00\nCompleted At: 2026-11-14T15:09:21-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Ultra-fast ~120s GPU-0 completion for Turn 12 (author: gemini):\n1. Uses ALREADY-SAVED `code/data/t12_tri_stats.pt` (Entry 1).\n2. Captures exact RoPE-free `ao_in`, `sig_o`, `mlp_act`, `sig_d` at `cap_pos` on 18 stratified distinct `safe_s1`\n fit calls (`6 pre + 6 post_work + 6 pre_sub`, zero Stage-2 contact, zero outcome labels) + phase-matched teachers,\n solves 4-fold OOF Empirical-Bayes-shrunk rank-8 `o_proj + down_proj` across `L5..58` (`108` matrices) with\n `lam_pres=6.0` syntax/BOS preserve penalty in ~4s, and saves `code/data/t12_mk_stats.pt` (Entry 2).\n3. Evaluates `e1_tri_s` + `ctrl` and `e2_mk_s` + `ctrl` on all 15 unseen `safe_s1` held-out calls + 8 exact\n unseen `closeprobe` call records (`mirror=True`, exact vLLM bf16 arithmetic), saving `scratch/t12_phase_a_report.json`.\n\"\"\"\nimport gc, json, os, pathlib, sys, time\nos.environ[\"G31_ATT_BUDGET\"] = \"4.0e8\"\n[... 229 lines cut ...]\n for cls_id in bp[\"cap_cls\"]:\n if cls_id == CLS_THOUGHT:\n continue\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2lssh -o BatchMode=yes wrx90 'head -n 120 /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/87/output.txt"},{"i":88,"kind":"raw","long":false,"text":":(bot-06206167-8ca0-40ec-a6a4-92114a51e382B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\n2(bot-06206167-8ca0-40ec-a6a4-92114a51e382:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"121,225p\\\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read rest of t12_final_gpu_90s.py\"}:"},{"i":89,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'sed -n \\\"121,225p\\\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read rest of t12_final_gpu_90s.py\"}:\nrssh -o BatchMode=yes wrx90 'sed -n \"121,225p\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py'\nS\n'Created At: 2026-11-14T15:09:34-05:00\nCompleted At: 2026-11-14T15:09:36-05:00\nCommand exited with code 0.\n\nCommand output:\n w_pr_c.append(2.2 if cls_id in (CLS_TOOL_DELIM, CLS_BOS) else (1.2 if cls_id == CLS_TOOL_ARG else 0.8))\n pr_w_list.append(torch.tensor(w_pr_c, dtype=torch.float32))\n folds_th_list.append(torch.full((int(th_m.sum()),), ci % 4, dtype=torch.long))\n folds_pr_list.append(torch.full((int(pr_m.sum()),), ci % 4, dtype=torch.long))\n\n tap_state[\"active\"] = True\n tap_state[\"pos\"] = torch.as_tensor(cap_pos, dtype=torch.long, device=\"cuda:0\")\n tap_state[\"ao_in\"] = {}\n tap_state[\"sig_o\"] = {}\n\n rb = model.forward(\n ids_base, out_pos=[cap_pos[-1]],\n[... 199 lines cut ...]\n torch.cuda.empty_cache()\n\n # Restore unhooked model.lin for clean adapter evaluation!\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2rssh -o BatchMode=yes wrx90 'sed -n \"121,225p\" /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_final_gpu_90s.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/89/output.txt"},{"i":90,"kind":"raw","long":false,"text":":(bot-30df9dc7-0e39-42b6-b098-ac791924fd8bB!\n\tsessionID\nThe code snippet seems to be related to some kind of incremental target generation within a specific range. Lines 165-182 suggest a loop iterating from 5 to 58. The loop appears to be processing data associated with `sl_auth_by_l`. The comment mentions direct and damped incremental targets.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-30df9dc7-0e39-42b6-b098-ac791924fd8b:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_x006_failures.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read deep_x006_failures.py on wrx90\"}:"},{"i":91,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_x006_failures.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read deep_x006_failures.py on wrx90\"}:\nessh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_x006_failures.py'\nj\n3Created At: 2026-11-14T15:09:51-05:00\nCompleted At: 2026-11-14T15:09:53-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Deep inspection of x006 e0044 failures, agent_error strings, and t9_stats.pt per-layer profile.\nStrictly Stage-2-disjoint (safe_v2 only).\n\"\"\"\nimport json\nimport pathlib\nimport subprocess\nimport sys\nfrom collections import Counter\n\nimport torch\n\n[... 255 lines cut ...]\n\nif __name__ == \"__main__\":\n main()\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2essh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/deep_x006_failures.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/91/output.txt"},{"i":92,"kind":"raw","long":true,"text":"p\n$[Message] timestamp=2026-11-14T20:09:42Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-81 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-81\" finished with result:\nCommand exited with code 0.\n\nCommand output:\n=== 14 Unedited x2 Runs (1666 episodes on 119 Stage-2-disjoint tasks) ===\n SOLVED: 1090 (65.4% -> 77.86/119 per run)\n WRONG_CLEAN : 348 ( 60.4% of failures, 24.86/run)\n CUTOFF_DIFF : 144 ( 25.0% of failures, 10.29/run)\n EMPTY_LIMIT : 73 ( 12.7% of failures, 5.21/run)\n EMPTY_FINISHED : 11 ( 1.9% of failures, 0.79/run)\n WRONG_CLEAN medians: toks=9089, calls=23.0, reads=7.0, edits=2.0, failed_tests=1.0\n CUTOFF/EMPTY_LIM medians: toks=16759, calls=35.0, aerr={'Agent exceeded session timeout (7.5 min)': 216, 'Agent exceeded turns budget (80 turns)': 1}\n\n=== Tasks with 0 < uned_rate <= 0.85 OR solved by an edit at 0/14 ===\nTask | uSol | uWC | uCut | 43 44 48 50 55 56\n[task] | 0/14| 0 | 14 | 0 1 0 0 0 0\n[task] | 0/14| 8 | 6 | 0 1 0 0 0 0\n[task] | 0/14| 14 | 0 | 0 0 1 0 0 0\n[task] | 1/14| 1 | 12 | 0 0 0 1 0 0\n[... 143 lines cut ...]\n [task] (13/14) -> 56:WRON\n [task] (14/14) -> 55:WRON\n [task] (13/14) -> 48:CUTO\n [task] (13/14) -> 55:WRON\n[line removed by the dashboard scrubber]\n [task] (14/14) -> 44:CUTO\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-81.log"},{"i":93,"kind":"raw","long":false,"text":":(bot-342cac97-4296-4a3a-85c9-e4c9162ac742B!\n\tsessionID\nThe output of the comparison script highlights a significant difference in the values of `x009` compared to `x006` and `x008`. The core discrepancy appears to be in the magnitude of those values, and understanding this variance is critical to diagnosing the root cause. Further investigation is needed to determine the reason for the inflated values in `x009`.\n\n\nThe analysis reveals that `x009`'s inflated values stem from a few outlier successes across specific tasks, not systemic performance differences. These successful tasks are masking the underlying trend. Further analysis of the cutoff-dominated failures, particularly tasks like `[task]`, might reveal underlying root causes.\n\n\nThe analysis focuses on tasks showing high `uWC` (wrong clean) failures and reliable tasks (13-14 successes). Examining tasks exclusively solved by a specific value, like task `[task]`, shows `uWC=8` and is solved only by a particular value. This pattern suggests that specific tasks are sensitive to the chosen configuration, failing on almost all attempts but succeeding with that value.\n\n\nSeveral tasks show a strong dependence on specific configurations, succeeding only with particular values and failing with others, suggesting sensitivity to configuration settings. Tasks solved by specific values, like the `readthedocs` task, highlight this issue. Further, comparing failures across the board revealed that some configurations disrupt otherwise reliable tasks, particularly through \"WRONG_CLEAN\" failures, indicating unintended side effects of those settings.\n\n\nAnalyzing regressions on a high number of tasks reveals that one specific configuration solves a larger subset with significantly fewer regressions on previously reliable tasks, indicating a potential configuration issue in other setups. A focused comparison against this performing configuration identifies specific tasks failing, potentially due to configuration-specific side effects. Initial assessment of these outliers suggests an advantage gained by specific configurations on the problematic tasks.\n\n\n2(bot-342cac97-4296-4a3a-85c9-e4c9162ac742:H\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]"},{"i":94,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n#!/usr/bin/env python3\n\"\"\"Inspect actual traces of chronic WRONG_CLEAN and CUTOFF failures on valid119 (zero Stage-2 contact).\"\"\"\nimport json\nimport pathlib\nfrom forensic_t15_x009 import load_safe_sets\n\nR = pathlib.Path(\"/home/keith/gemma-v2\")\nBATCHES = R / \"results/wsp31/batches\"\n\n\ndef show_ep(batch: str, arm: str, iid: str):\n rb = BATCHES / batch / arm / \"rebench/shard0_gpu0\"\n rows = {json.loads(l)[\"instance_id\"]: json.loads(l) for l in (rb / \"task_results.jsonl\").read_text().splitlines() if l.strip()}\n r = rows[iid]\n td = json.loads((rb / \"traces\" / f\"trace_{iid}.json\").read_text())\n steps = [s for s in td[\"steps\"] if s.get(\"source\") == \"agent\"]\n grade = r.get(\"grade\") or {}\n[line removed by the dashboard scrubber]\n[... 121 lines cut ...]\n4 (\"x006\", \"e0044\", \"[task]\"),\n8\n4 (\"b010\", \"e0048\", \"[task]\"),\nP\nL (\"x006\", \"e0044\", \"mewwts__addict.75284f95.combine_file__3fttj8ti\"),\nL\nH (\"x006\", \"e0044\", \"jd__tenacity.0d40e76f.func_basic__85q611gl\"),\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/94/output.txt"},{"i":95,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:10:35-05:00\nCompleted At: 2026-11-14T15:10:39-05:00\nCommand exited with code 0.\n\nCommand output:\n\n=== x006/base :: [task] | resolved=False tok=20000 calls=34 aerr=Agent exceeded session timeout (7.5 min) status={'FAILED': 2, 'PASSED': 113, 'SKIPPED': 4} ===\n Calls: 0:run_command(python3 - <<'PY'\nfrom gammapy.maps import Wcs)[th=0c] -> 1:run_command(ls gammapy/version.py)[th=0c] -> 2:run_command(ls -F gammapy/)[th=0c] -> 3:read_file()[th=0c] -> 4:read_file()[th=0c] -> 5:run_command(grep -rn \"gammapy.version\" .)[th=0c] -> 6:run_command(echo \"version = '1.0.0'\" > gammapy/version.py)[th=0c] -> 7:run_command(python3 - <<'PY'\nfrom gammapy.maps import Wcs)[th=0c] -> 8:run_command(python3 - <<'PY'\nimport sys\nimport os\n# Remov)[th=0c] -> 9:run_command(cd /tmp && python3 - <<'PY'\nfrom gammapy.maps)[th=0c] -> 10:run_command(python3 -c \"import gammapy; print(gammapy.__f)[th=0c] -> 11:run_command(find / -name \"fit_statistics_cython*.so\" 2>/d)[th=0c] -> 12:run_command(grep -rn \"from gammapy.stats.fit_statistics_c)[th=0c] -> 13:run_command(mkdir -p gammapy/stats && touch gammapy/stats)[th=0c] -> 14:run_command(python3 - <<'PY'\n[... 384 lines cut ...]\nimport tenacity\nfrom tenacit)[th=0c] -> 36:run_command(grep -rn \"\\.reraise()\" tenacity/__init__.py)[th=0c] -> 37:get_status()[th=0c] -> 38:run_command(git status --short && git diff)[th=0c] -> 39:submit_patch()[th=0c] -> 40:NO_TC[th=0c,msg=392c] -> 41:NO_TC[th=0c,msg=346c]\n [Last thought -> NO_TC]: ...\n [Last thought -> NO_TC]: ...\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n[line removed by the dashboard scrubber]\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt"},{"i":96,"kind":"raw","long":true,"text":":(bot-af945648-a3b8-41ed-a763-35fb388cb11aB!\n\tsessionID\nThe output file highlights `mewwts__addict` and `jd__tenacity` within distinct call chains. Re-examining these call chains seems critical given the failure count associated with `mewwts__addict.75284f95.combine_file__3fttj8ti`. A deeper look into the interactions of these calls is needed.\n\n\nThe analysis reveals a pattern: both `mewwts__addict` and `jd__tenacity` call chains bypass the repository's test suite (`pytest`), instead relying on isolated `python3 -c` executions. This oversight leads to undetected regressions, with 8 failures in the former and 2 in the latter. The repeated failure to integrate existing tests suggests the test suite is not being correctly incorporated into the workflow.\n\n\n2(bot-af945648-a3b8-41ed-a763-35fb388cb11a:\n{\"EndLine\":135,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt\",\"StartLine\":45}:\n{\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Check exact behavioral discriminators between SOLVED and WRONG_CLEAN on valid119 across x003..x009.\\\"\\\"\\\"\\nimport json\\nimport pathlib\\nfrom collections import Counter\\nfrom forensic_t15_x009 import load_safe_sets\\n\\nR = pathlib.Path(\\\"/home/keith/gemma-v2\\\")\\nBATCHES = R / \\\"results/wsp31/batches\\\"\\n\\n\\ndef inspect_wrong_clean_patterns(batch: str, arm: str, valid119: set[str]):\\n rb = BATCHES / batch / arm / \\\"rebench/shard0_gpu0\\\"\\n rows = {json.loads(l)[\\\"instance_id\\\"]: json.loads(l) for l in (rb / \\\"task_results.jsonl\\\").read_text().splitlines() if l.strip()}\\n stats = Counter()\\n wc_examples = []\\n for iid in sorted(valid119):\\n r = rows[iid]\\n resolved = bool(r.get(\\\"resolved\\\"))\\n aerr = str(r.get(\\\"agent_error\\\") or \\\"\\\")\\n pchars = int(r.get(\\\"patch_chars\\\", 0) or 0)\\n if resolved or aerr or pchars == 0:\\n continue\\n # WRONG_CLEAN!\\n stats[\\\"total_wc\\\"] += 1\\n td = json.loads((rb / \\\"traces\\\" / f\\\"trace_{iid}.json\\\").read_text())\\n steps = [s for s in td[\\\"steps\\\"] if s.get(\\\"source\\\") == \\\"agent\\\" and s.get(\\\"tool_calls\\\")]\\n last_edit = -1\\n ran_repo_test_ever = False\\n ran_repo_test_after_edit = False\\n ran_toy_py_after_edit = False\\n read_test_file = False\\n edited_test_file = False\\n grep_callers = False\\n for ci, s in enumerate(steps):\\n tc = s[\\\"tool_calls\\\"][0]\\n fn = tc.get(\\\"function_name\\\", \\\"\\\")\\n args = tc.get(\\\"arguments\\\") or {}\\n astr = json.dumps(args)\\n if fn in (\\\"edit_file\\\", \\\"write_file\\\"):\\n last_edit = ci\\n if \\\"test\\\" in str(args.get(\\\"path\\\", \\\"\\\")).lower():\\n edited_test_file = True\\n elif fn == \\\"read_file\\\":\\n if \\\"test\\\" in str(args.get(\\\"path\\\", \\\"\\\")).lower():\\n read_test_file = True\\n elif fn == \\\"run_command\\\":\\n cmd = str(args.get(\\\"command\\\", \\\"\\\"))\\n if any(k in cmd for k in (\\\"pytest\\\", \\\"unittest\\\", \\\"nosetests\\\", \\\"tox\\\")):\\n ran_repo_test_ever = True\\n if \\\"grep\\\" in cmd or \\\"rg \\\" in cmd:\\n grep_callers = True\\n for ci in range(last_edit + 1, len(steps)):\\n tc = steps[ci][\\\"tool_calls\\\"][0]\\n fn = tc.get(\\\"function_name\\\", \\\"\\\")\\n cmd = str((tc.get(\\\"arguments\\\") or {}).get(\\\"command\\\", \\\"\\\"))\\n if fn == \\\"run_command\\\":\\n if any(k in cmd for k in (\\\"pytest\\\", \\\"unittest\\\", \\\"nosetests\\\", \\\"tox\\\")):\\n ran_repo_test_after_edit = True\\n elif \\\"python\\\" in cmd:\\n ran_toy_py_after_edit = True\\n if not ran_repo_test_ever:\\n stats[\\\"never_ran_pytest\\\"] += 1\\n if not ran_repo_test_after_edit:\\n stats[\\\"no_pytest_after_last_edit\\\"] += 1\\n if ran_toy_py_af\n[... 1579 characters cut ...]"},{"i":97,"kind":"raw","long":true,"text":"{\"EndLine\":135,\"Path\":\"C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt\",\"StartLine\":45}:\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt\n;\n8Created At: 2026-11-14T15:10:57-05:00\nCompleted At: 2026-11-14T15:11:09-05:00\nShowing lines 45-135 of 250\n45: import sys\n46: import types\n47: \n48: # M)[th=0c] -> 12:run_command(grep -rn \"from .fit_statistics_cython import\")[th=0c] -> 13:read_file()[th=0c] -> 14:run_command(python3 - <<'PY'\n49: import sys\n50: import types\n51: \n52: # M)[th=0c] -> 15:run_command(python3 - <<'PY'\n53: import sys\n54: import types\n55: \n56: # M)[th=0c] -> 16:read_file()[th=0c] -> 17:run_command(grep -n \"class PiecewiseNormSpatialModel\" gam)[th=0c]\n57: ... : 18:read_file()[th=0c] -> 19:run_command(python3 - <<'PY'\n58: import sys\n[... 72 lines cut ...]\n131: with open('src/pi)[th=0c] -> 29:read_file()[th=0c] -> 30:edit_file()[th=0c] -> 31:read_file()[th=0c] -> 32:write_file()[th=0c] -> 33:run_command(pytest tests/test_exclude_dependencies.py -q )[th=0c] -> 34:run_command(grep -rn \"class PackageNode\" src/pipdeptree/)[th=0c] -> 35:read_file()[th=0c] -> 36:read_file()[th=0c] -> 37:edit_file()[th=0c] -> 38:NO_TC[th=0c,msg=29c] -> 39:NO_TC[th=0c,msg=988c]\n132: [Last thought -> NO_TC]: ...\n133: [Last thought -> NO_TC]: ...\n134: \n135: === x006/e0044 :: [task] | resolved=False tok=20000 calls=23 aerr=Agent exceeded session timeout (7.5 min) status={'FAILED': 78, 'PASSED': 301, 'SKIPPED': 10} ===\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nwC:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/95/output.txt -("},{"i":98,"kind":"raw","long":true,"text":"{\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Check exact behavioral discriminators between SOLVED and WRONG_CLEAN on valid119 across x003..x009.\\\"\\\"\\\"\\nimport json\\nimport pathlib\\nfrom collections import Counter\\nfrom forensic_t15_x009 import load_safe_sets\\n\\nR = pathlib.Path(\\\"/home/keith/gemma-v2\\\")\\nBATCHES = R / \\\"results/wsp31/batches\\\"\\n\\n\\ndef inspect_wrong_clean_patterns(batch: str, arm: str, valid119: set[str]):\\n rb = BATCHES / batch / arm / \\\"rebench/shard0_gpu0\\\"\\n rows = {json.loads(l)[\\\"instance_id\\\"]: json.loads(l) for l in (rb / \\\"task_results.jsonl\\\").read_text().splitlines() if l.strip()}\\n stats = Counter()\\n wc_examples = []\\n for iid in sorted(valid119):\\n r = rows[iid]\\n resolved = bool(r.get(\\\"resolved\\\"))\\n aerr = str(r.get(\\\"agent_error\\\") or \\\"\\\")\\n pchars = int(r.get(\\\"patch_chars\\\", 0) or 0)\\n if resolved or aerr or pchars == 0:\\n continue\\n # WRONG_CLEAN!\\n stats[\\\"total_wc\\\"] += 1\\n td = json.loads((rb / \\\"traces\\\" / f\\\"trace_{iid}.json\\\").read_text())\\n steps = [s for s in td[\\\"steps\\\"] if s.get(\\\"source\\\") == \\\"agent\\\" and s.get(\\\"tool_calls\\\")]\\n last_edit = -1\\n ran_repo_test_ever = False\\n ran_repo_test_after_edit = False\\n ran_toy_py_after_edit = False\\n read_test_file = False\\n edited_test_file = False\\n grep_callers = False\\n for ci, s in enumerate(steps):\\n tc = s[\\\"tool_calls\\\"][0]\\n fn = tc.get(\\\"function_name\\\", \\\"\\\")\\n args = tc.get(\\\"arguments\\\") or {}\\n astr = json.dumps(args)\\n if fn in (\\\"edit_file\\\", \\\"write_file\\\"):\\n last_edit = ci\\n if \\\"test\\\" in str(args.get(\\\"path\\\", \\\"\\\")).lower():\\n edited_test_file = True\\n elif fn == \\\"read_file\\\":\\n if \\\"test\\\" in str(args.get(\\\"path\\\", \\\"\\\")).lower():\\n read_test_file = True\\n elif fn == \\\"run_command\\\":\\n cmd = str(args.get(\\\"command\\\", \\\"\\\"))\\n if any(k in cmd for k in (\\\"pytest\\\", \\\"unittest\\\", \\\"nosetests\\\", \\\"tox\\\")):\\n ran_repo_test_ever = True\\n if \\\"grep\\\" in cmd or \\\"rg \\\" in cmd:\\n grep_callers = True\\n for ci in range(last_edit + 1, len(steps)):\\n tc = steps[ci][\\\"tool_calls\\\"][0]\\n fn = tc.get(\\\"function_name\\\", \\\"\\\")\\n cmd = str((tc.get(\\\"arguments\\\") or {}).get(\\\"command\\\", \\\"\\\"))\\n if fn == \\\"run_command\\\":\\n if any(k in cmd for k in (\\\"pytest\\\", \\\"unittest\\\", \\\"nosetests\\\", \\\"tox\\\")):\\n ran_repo_test_after_edit = True\\n elif \\\"python\\\" in cmd:\\n ran_toy_py_after_edit = True\\n if not ran_repo_test_ever:\\n stats[\\\"never_ran_pytest\\\"] += 1\\n if not ran_repo_test_after_edit:\\n stats[\\\"no_pytest_after_last_edit\\\"] += 1\\n if ran_toy_py_after_edit and not ran_repo_test_after_edit:\\n stats[\\\"only_toy_py_no_pytest\\\"] += 1\\n if not read_test_file:\\n stats[\\\"never_read_test_file\\\"] += 1\\n if edited_test_file:\\n stats[\\\"edited_test_file\\\"] += 1\\n sc = (r.get(\\\"grade\\\") or {}).get(\\\"status_counts\\\") or {}\\n ft = int(sc.get(\\\"FAILED\\\", 0) or 0) + int(sc.get(\\\"ERROR\\\", 0) or 0)\\n if ft == 1:\\n stats[\\\"failed_1_test\\\"] += 1\\n elif ft \\u003c= 3:\\n stats[\\\"failed_2_3_tests\\\"] += 1\\n else:\\n stats[\\\"failed_4plus_tests\\\"] += 1\\n print(f\\\"{batch}/{arm:5s}: {dict(stats)}\\\")\\n\\n\\ndef main():\\n _, _, valid119 = load_safe_sets()\\n for b, a in [\\n (\\\"x006\\\", \\\"base\\\"), (\\\"x006\\\", \\\"e0043\\\"), (\\\"x006\\\", \\\"e0044\\\"),\\n (\\\"b010\\\", \\\"base\\\"), (\\\"b010\\\", \\\"e0048\\\"),\\n (\\\"x008\\\", \\\"base\\\"), (\\\"x008\\\", \\\"e0050\\\"),\\n (\\\"x009\\\", \\\"base\\\"), (\\\"x009\\\", \\\"e0055\\\"), (\\\"x\n[... 1323 characters cut ...]"},{"i":99,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\wc_patterns_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/wc_patterns_t15.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/wc_patterns_t15.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Analyze WRONG_CLEAN patterns across batches\"}2\n+Analyze WRONG_CLEAN patterns across batches\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\wc_patterns_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/wc_patterns_t15.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/wc_patterns_t15.py'\nCreated At: 2026-11-14T15:11:09-05:00\nCompleted At: 2026-11-14T15:11:14-05:00\nCommand exited with code 0.\n\nCommand output:\nx006/base : {'total_wc': 23, 'never_read_test_file': 23, 'failed_2_3_tests': 6, 'never_ran_pytest': 5, 'no_pytest_after_last_edit': 6, 'only_toy_py_no_pytest': 6, 'failed_1_test': 13, 'failed_4plus_tests': 4}\nx006/e0043: {'total_wc': 27, 'never_ran_pytest': 6, 'no_pytest_after_last_edit': 8, 'only_toy_py_no_pytest': 6, 'never_read_test_file': 27, 'failed_4plus_tests': 6, 'failed_1_test': 17, 'failed_2_3_tests': 4}\nx006/e0044: {'total_wc': 24, 'never_read_test_file': 24, 'failed_2_3_tests': 6, 'failed_1_test': 15, 'never_ran_pytest': 7, 'no_pytest_after_last_edit': 8, 'only_toy_py_no_pytest': 5, 'failed_4plus_tests': 3}\nb010/base : {'total_wc': 24, 'never_ran_pytest': 8, 'no_pytest_after_last_edit': 9, 'only_toy_py_no_pytest': 7, 'never_read_test_file': 24, 'failed_2_3_tests': 7, 'failed_1_test': 12, 'failed_4plus_tests': 5}\nb010/e0048: {'total_wc': 22, 'never_read_test_file': 22, 'failed_1_test': 11, 'failed_2_3_tests': 7, 'never_ran_pytest': 6, 'no_pytest_after_last_edit': 6, 'only_toy_py_no_pytest': 6, 'failed_4plus_tests': 4}\nx008/base : {'total_wc': 27, 'never_ran_pytest': 7, 'no_pytest_after_last_edit': 10, 'only_toy_py_no_pytest': 9, 'never_read_test_file': 27, 'failed_2_3_tests': 6, 'failed_1_test': 16, 'failed_4plus_tests': 5}\nx008/e0050: {'total_wc': 26, 'never_ran_pytest': 6, 'no_pytest_after_last_edit': 6, 'only_toy_py_no_pytest': 6, 'never_read_test_file': 26, 'failed_2_3_tests': 8, 'failed_1_test': 12, 'failed_4plus_tests': 6}\nx009/base : {'total_wc': 25, 'never_read_test_file': 25, 'failed_2_3_tests': 8, 'failed_1_test': 13, 'no_pytest_after_last_edit': 7, 'never_ran_pytest': 5, 'only_toy_py_no_pytest': 5, 'failed_4plus_tests': 4}\nx009/e0055: {'total_wc': 39, 'never_ran_pytest': 14, 'no_pytest_after_last_edit': 16, 'only_toy_py_no_pytest': 14, 'never_read_test_file': 39, 'failed_4plus_tests': 11, 'failed_2_3_tests': 13, 'failed_1_test': 15}\nx009/e0056: {'total_wc': 24, 'never_read_test_file': 24, 'failed_2_3_tests': 6, 'failed_1_test': 16, 'never_ran_pytest': 5, 'no_pytest_after_last_edit': 5, 'only_toy_py_no_pytest': 3, 'failed_4plus_tests': 2}\nterminalJ-\n+analyze WRONG_CLEAN patterns across batchesR\n[... 7 lines cut ...]\nx008/e0050: {'total_wc': 26, 'never_ran_pytest': 6, 'no_pytest_after_last_edit': 6, 'only_toy_py_no_pytest': 6, 'never_read_test_file': 26, 'failed_2_3_tests': 8, 'failed_1_test': 12, 'failed_4plus_tests': 6}\nx009/base : {'total_wc': 25, 'never_read_test_file': 25, 'failed_2_3_tests': 8, 'failed_1_test': 13, 'no_pytest_after_last_edit': 7, 'never_ran_pytest': 5, 'only_toy_py_no_pytest': 5, 'failed_4plus_tests': 4}\nx009/e0055: {'total_wc': 39, 'never_ran_pytest': 14, 'no_pytest_after_last_edit': 16, 'only_toy_py_no_pytest': 14, 'never_read_test_file': 39, 'failed_4plus_tests': 11, 'failed_2_3_tests': 13, 'failed_1_test': 15}\nx009/e0056: {'total_wc': 24, 'never_read_test_file': 24, 'failed_2_3_tests': 6, 'failed_1_test': 16, 'never_ran_pytest': 5, 'no_pytest_after_last_edit': 5, 'only_toy_py_no_pytest': 3, 'failed_4plus_tests': 2}\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\wc_patterns_t15.py wrx90:/ho\n[... 361 characters cut ...]"},{"i":100,"kind":"raw","long":false,"text":":(bot-96155bb5-3fb8-439c-ab3e-9a6171ebf9c8B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\nThe analysis of the ledger records and batch comparisons points to potential issues beyond the file path argument. The high failure rates in `x009/e0055` suggest a significant discrepancy compared to `x009/base` and `x009/e0056`, specifically related to how often Pytest is run and how many tests fail. The investigation needs to expand beyond the initial path argument suspicion, including examining the environment in which the tests run. The clock shows that there is still much time available for analysis.\n\n\nInitial calculation indicates a long GPU wait time, around 8 hours, for a specific process. Upon reviewing the status, that process is consuming GPU 0 for an extended duration. Re-evaluating the CPU's capabilities, considering earlier benchmarks, the possibility of running specific tasks (mirror=True, g31) on CPU becomes a hypothesis worth investigation. The CPU has a significant number of cores and available RAM.\n\n\n2(bot-96155bb5-3fb8-439c-ab3e-9a6171ebf9c8:.\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \\\"cf001\\\" $R/wsp31/queue/STATUS.md; $PY -c \\\"\\nimport os, sys, time\\nos.environ[\\\\\\\"CUDA_VISIBLE_DEVICES\\\\\\\"] = \\\\\\\"\\\\\\\"\\nimport torch, torch.nn.functional as F\\ntorch.set_num_threads(40)\\nsys.path.insert(0, \\\\\\\"/home/keith/gemma-v2/wsp31/tools\\\\\\\")\\nimport g31\\nt0 = time.time()\\nm = g31.G31(device=\\\\\\\"cpu\\\\\\\", mirror=True, cache_dense=False)\\nseqs = [torch.ones((3000, 5376), dtype=torch.bfloat16) for _ in range(16)]\\nt1 = time.time()\\nfor l in [5, 6]:\\n d = m.L[l]; g = m.arch.geom(l); hd, kv = g[\\\\\\\"head_dim\\\\\\\"], g[\\\\\\\"kv_heads\\\\\\\"]\\n wq, wk, wv, wo = m.base_weight(l, \\\\\\\"q_proj\\\\\\\"), m.base_weight(l, \\\\\\\"k_proj\\\\\\\"), m.base_weight(l, \\\\\\\"v_proj\\\\\\\"), m.base_weight(l, \\\\\\\"o_proj\\\\\\\")\\n wg, wu, wd = m.base_weight(l, \\\\\\\"gate_proj\\\\\\\"), m.base_weight(l, \\\\\\\"up_proj\\\\\\\"), m.base_weight(l, \\\\\\\"down_proj\\\\\\\")\\n for i in range(16):\\n h = seqs[i]\\n x = m.rms(h, d[\\\\\\\"input_layernorm\\\\\\\"])\\n q = m.rms(F.linear(x, wq).unflatten(-1, (32, hd)), d[\\\\\\\"q_norm\\\\\\\"])\\n k = m.rms(F.linear(x, wk).unflatten(-1, (kv, hd)), d[\\\\\\\"k_norm\\\\\\\"])\\n v = m.rms(F.linear(x, wv).unflatten(-1, (kv, hd)))\\n q, k = m.rope(l, q), m.rope(l, k)\\n ao = m.attention(q, k, v, g[\\\\\\\"window\\\\\\\"])\\n h = h + m.rms(F.linear(ao, wo), d[\\\\\\\"post_attention_layernorm\\\\\\\"])\\n xm = m.rms(h, d[\\\\\\\"pre_feedforward_layernorm\\\\\\\"])\\n act = g31.gelu_tanh(F.linear(xm, wg)) * F.linear(xm, wu)\\n seqs[i] = (h + m.rms(F.linear(act, wd), d[\\\\\\\"post_feedforward_layernorm\\\\\\\"])) * d[\\\\\\\"layer_scalar\\\\\\\"]\\n del wq, wk, wv, wo, wg, wu, wd\\ndt = time.time() - t1\\nprint(f\\\\\\\"2 layers x 16 seqs (3000 tok): {dt:.2f}s -\\u003e est 60 layers = {dt*30:.1f}s\\\\\\\")\\n\\\"'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Benchmark layerwise 16-seq g31 on CPU\"}:"},{"i":101,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \\\"cf001\\\" $R/wsp31/queue/STATUS.md; $PY -c \\\"\\nimport os, sys, time\\nos.environ[\\\\\\\"CUDA_VISIBLE_DEVICES\\\\\\\"] = \\\\\\\"\\\\\\\"\\nimport torch, torch.nn.functional as F\\ntorch.set_num_threads(40)\\nsys.path.insert(0, \\\\\\\"/home/keith/gemma-v2/wsp31/tools\\\\\\\")\\nimport g31\\nt0 = time.time()\\nm = g31.G31(device=\\\\\\\"cpu\\\\\\\", mirror=True, cache_dense=False)\\nseqs = [torch.ones((3000, 5376), dtype=torch.bfloat16) for _ in range(16)]\\nt1 = time.time()\\nfor l in [5, 6]:\\n d = m.L[l]; g = m.arch.geom(l); hd, kv = g[\\\\\\\"head_dim\\\\\\\"], g[\\\\\\\"kv_heads\\\\\\\"]\\n wq, wk, wv, wo = m.base_weight(l, \\\\\\\"q_proj\\\\\\\"), m.base_weight(l, \\\\\\\"k_proj\\\\\\\"), m.base_weight(l, \\\\\\\"v_proj\\\\\\\"), m.base_weight(l, \\\\\\\"o_proj\\\\\\\")\\n wg, wu, wd = m.base_weight(l, \\\\\\\"gate_proj\\\\\\\"), m.base_weight(l, \\\\\\\"up_proj\\\\\\\"), m.base_weight(l, \\\\\\\"down_proj\\\\\\\")\\n for i in range(16):\\n h = seqs[i]\\n x = m.rms(h, d[\\\\\\\"input_layernorm\\\\\\\"])\\n q = m.rms(F.linear(x, wq).unflatten(-1, (32, hd)), d[\\\\\\\"q_norm\\\\\\\"])\\n k = m.rms(F.linear(x, wk).unflatten(-1, (kv, hd)), d[\\\\\\\"k_norm\\\\\\\"])\\n v = m.rms(F.linear(x, wv).unflatten(-1, (kv, hd)))\\n q, k = m.rope(l, q), m.rope(l, k)\\n ao = m.attention(q, k, v, g[\\\\\\\"window\\\\\\\"])\\n h = h + m.rms(F.linear(ao, wo), d[\\\\\\\"post_attention_layernorm\\\\\\\"])\\n xm = m.rms(h, d[\\\\\\\"pre_feedforward_layernorm\\\\\\\"])\\n act = g31.gelu_tanh(F.linear(xm, wg)) * F.linear(xm, wu)\\n seqs[i] = (h + m.rms(F.linear(act, wd), d[\\\\\\\"post_feedforward_layernorm\\\\\\\"])) * d[\\\\\\\"layer_scalar\\\\\\\"]\\n del wq, wk, wv, wo, wg, wu, wd\\ndt = time.time() - t1\\nprint(f\\\\\\\"2 layers x 16 seqs (3000 tok): {dt:.2f}s -\\u003e est 60 layers = {dt*30:.1f}s\\\\\\\")\\n\\\"'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Benchmark layerwise 16-seq g31 on CPU\"}:\nssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \"cf001\" $R/wsp31/queue/STATUS.md; $PY -c \"\nimport os, sys, time\nos.environ[\\\"CUDA_VISIBLE_DEVICES\\\"] = \\\"\\\"\nimport torch, torch.nn.functional as F\ntorch.set_num_threads(40)\nsys.path.insert(0, \\\"/home/keith/gemma-v2/wsp31/tools\\\")\nimport g31\nt0 = time.time()\nm = g31.G31(device=\\\"cpu\\\", mirror=True, cache_dense=False)\nseqs = [torch.ones((3000, 5376), dtype=torch.bfloat16) for _ in range(16)]\nt1 = time.time()\nfor l in [5, 6]:\n d = m.L[l]; g = m.arch.geom(l); hd, kv = g[\\\"head_dim\\\"], g[\\\"kv_heads\\\"]\n wq, wk, wv, wo = m.base_weight(l, \\\"q_proj\\\"), m.base_weight(l, \\\"k_proj\\\"), m.base_weight(l, \\\"v_proj\\\"), m.base_weight(l, \\\"o_proj\\\")\n wg, wu, wd = m.base_weight(l, \\\"gate_proj\\\"), m.base_weight(l, \\\"up_proj\\\"), m.base_weight(l, \\\"down_proj\\\")\n for i in range(16):\n h = seqs[i]\n x = m.rms(h, d[\\\"input_layernorm\\\"])\n q = m.rms(F.linear(x, wq).unflatten(-1, (32, hd)), d[\\\"q_norm\\\"])\n[... 80 lines cut ...]\n xm = m.rms(h, d[\\\"pre_feedforward_layernorm\\\"])\n act = g31.gelu_tanh(F.linear(xm, wg)) * F.linear(xm, wu)\n seqs[i] = (h + m.rms(F.linear(act, wd), d[\\\"post_feedforward_layernorm\\\"])) * d[\\\"layer_scalar\\\"]\n del wq, wk, wv, wo, wg, wu, wd\ndt = time.time() - t1\nprint(f\\\"2 layers x 16 seqs (3000 tok): {dt:.2f}s -> est 60 layers = {dt*30:.1f}s\\\")\n\"':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/101/output.txt"},{"i":102,"kind":"raw","long":false,"text":":(bot-67bca016-1a1c-4a7f-8cd0-3457bd89dcadB!\n\tsessionID\n2(bot-67bca016-1a1c-4a7f-8cd0-3457bd89dcad:\n{\"Content\":\"import os, sys, time\\nos.environ[\\\"CUDA_VISIBLE_DEVICES\\\"] = \\\"\\\"\\nimport torch\\nimport torch.nn.functional as F\\n\\ntorch.set_num_threads(40)\\nsys.path.insert(0, \\\"/home/keith/gemma-v2/wsp31/tools\\\")\\nimport g31\\n\\nm = g31.G31(device=\\\"cpu\\\", mirror=True, cache_dense=False)\\nseqs = [torch.ones((3000, 5376), dtype=torch.bfloat16) for _ in range(16)]\\nt1 = time.time()\\nfor l in [5, 6]:\\n t_dq = time.time()\\n d = m.L[l]\\n g = m.arch.geom(l)\\n hd, kv = g[\\\"head_dim\\\"], g[\\\"kv_heads\\\"]\\n wq, wk, wv, wo = m.base_weight(l, \\\"q_proj\\\"), m.base_weight(l, \\\"k_proj\\\"), m.base_weight(l, \\\"v_proj\\\"), m.base_weight(l, \\\"o_proj\\\")\\n wg, wu, wd = m.base_weight(l, \\\"gate_proj\\\"), m.base_weight(l, \\\"up_proj\\\"), m.base_weight(l, \\\"down_proj\\\")\\n dq_s = time.time() - t_dq\\n t_mm = time.time()\\n for i in range(16):\\n h = seqs[i]\\n x = m.rms(h, d[\\\"input_layernorm\\\"])\\n q = m.rms(F.linear(x, wq).unflatten(-1, (32, hd)), d[\\\"q_norm\\\"])\\n k = m.rms(F.linear(x, wk).unflatten(-1, (kv, hd)), d[\\\"k_norm\\\"])\\n v = m.rms(F.linear(x, wv).unflatten(-1, (kv, hd)))\\n q, k = m.rope(l, q), m.rope(l, k)\\n ao = m.attention(q, k, v, g[\\\"window\\\"])\\n h = h + m.rms(F.linear(ao, wo), d[\\\"post_attention_layernorm\\\"])\\n xm = m.rms(h, d[\\\"pre_feedforward_layernorm\\\"])\\n act = g31.gelu_tanh(F.linear(xm, wg)) * F.linear(xm, wu)\\n seqs[i] = (h + m.rms(F.linear(act, wd), d[\\\"post_feedforward_layernorm\\\"])) * d[\\\"layer_scalar\\\"]\\n mm_s = time.time() - t_mm\\n print(f\\\"L{l} (global={g['is_global']}): dequant={dq_s:.2f}s, 16x3000 compute={mm_s:.2f}s\\\", flush=True)\\n del wq, wk, wv, wo, wg, wu, wd\\ndt = time.time() - t1\\nprint(f\\\"Total 2 layers: {dt:.2f}s -\\u003e est 60 layers (10 glob + 50 slid) = {10*dq_s + 60*(dt/2):.1f}s\\\", flush=True)\\n\",\"Overwrite\":true,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\bench_layerwise_cpu.py\"}:\n{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \\\"cf001\\\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run CPU layerwise benchmark on wrx90\"}`"},{"i":103,"kind":"raw","long":true,"text":"{\"Content\":\"import os, sys, time\\nos.environ[\\\"CUDA_VISIBLE_DEVICES\\\"] = \\\"\\\"\\nimport torch\\nimport torch.nn.functional as F\\n\\ntorch.set_num_threads(40)\\nsys.path.insert(0, \\\"/home/keith/gemma-v2/wsp31/tools\\\")\\nimport g31\\n\\nm = g31.G31(device=\\\"cpu\\\", mirror=True, cache_dense=False)\\nseqs = [torch.ones((3000, 5376), dtype=torch.bfloat16) for _ in range(16)]\\nt1 = time.time()\\nfor l in [5, 6]:\\n t_dq = time.time()\\n d = m.L[l]\\n g = m.arch.geom(l)\\n hd, kv = g[\\\"head_dim\\\"], g[\\\"kv_heads\\\"]\\n wq, wk, wv, wo = m.base_weight(l, \\\"q_proj\\\"), m.base_weight(l, \\\"k_proj\\\"), m.base_weight(l, \\\"v_proj\\\"), m.base_weight(l, \\\"o_proj\\\")\\n wg, wu, wd = m.base_weight(l, \\\"gate_proj\\\"), m.base_weight(l, \\\"up_proj\\\"), m.base_weight(l, \\\"down_proj\\\")\\n dq_s = time.time() - t_dq\\n t_mm = time.time()\\n for i in range(16):\\n h = seqs[i]\\n x = m.rms(h, d[\\\"input_layernorm\\\"])\\n q = m.rms(F.linear(x, wq).unflatten(-1, (32, hd)), d[\\\"q_norm\\\"])\\n k = m.rms(F.linear(x, wk).unflatten(-1, (kv, hd)), d[\\\"k_norm\\\"])\\n v = m.rms(F.linear(x, wv).unflatten(-1, (kv, hd)))\\n q, k = m.rope(l, q), m.rope(l, k)\\n ao = m.attention(q, k, v, g[\\\"window\\\"])\\n h = h + m.rms(F.linear(ao, wo), d[\\\"post_attention_layernorm\\\"])\\n xm = m.rms(h, d[\\\"pre_feedforward_layernorm\\\"])\\n act = g31.gelu_tanh(F.linear(xm, wg)) * F.linear(xm, wu)\\n seqs[i] = (h + m.rms(F.linear(act, wd), d[\\\"post_feedforward_layernorm\\\"])) * d[\\\"layer_scalar\\\"]\\n mm_s = time.time() - t_mm\\n print(f\\\"L{l} (global={g['is_global']}): dequant={dq_s:.2f}s, 16x3000 compute={mm_s:.2f}s\\\", flush=True)\\n del wq, wk, wv, wo, wg, wu, wd\\ndt = time.time() - t1\\nprint(f\\\"Total 2 layers: {dt:.2f}s -\\u003e est 60 layers (10 glob + 50 slid) = {10*dq_s + 60*(dt/2):.1f}s\\\", flush=True)\\n\",\"Overwrite\":true,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\bench_layerwise_cpu.py\"}:\nimport os, sys, time\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"\nimport torch\nimport torch.nn.functional as F\n\ntorch.set_num_threads(40)\nsys.path.insert(0, \"/home/keith/gemma-v2/wsp31/tools\")\nimport g31\n\nm = g31.G31(device=\"cpu\", mirror=True, cache_dense=False)\nseqs = [torch.ones((3000, 5376), dtype=torch.bfloat16) for _ in range(16)]\nt1 = time.time()\nfor l in [5, 6]:\n t_dq = time.time()\n d = m.L[l]\n g = m.arch.geom(l)\n hd, kv = g[\"head_dim\"], g[\"kv_heads\"]\n wq, wk, wv, wo = m.base_weight(l, \"q_proj\"), m.base_weight(l, \"k_proj\"), m.base_weight(l, \"v_proj\"), m.base_weight(l, \"o_proj\")\n wg, wu, wd = m.base_weight(l, \"gate_proj\"), m.base_weight(l, \"up_proj\"), m.base_weight(l, \"down_proj\")\n[... 58 lines cut ...]\n@ act = g31.gelu_tanh(F.linear(xm, wg)) * F.linear(xm, wu)\ni\ne seqs[i] = (h + m.rms(F.linear(act, wd), d[\"post_feedforward_layernorm\"])) * d[\"layer_scalar\"]\nn\nj print(f\"L{l} (global={g['is_global']}): dequant={dq_s:.2f}s, 16x3000 compute={mm_s:.2f}s\", flush=True)\nu\nqprint(f\"Total 2 layers: {dt:.2f}s -> est 60 layers (10 glob + 50 slid) = {10*dq_s + 60*(dt/2):.1f}s\", flush=True)\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/103/output.txt"},{"i":104,"kind":"raw","long":false,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \\\"cf001\\\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run CPU layerwise benchmark on wrx90\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-104\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-104.log\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 99 | |\n[line removed by the dashboard scrubber]\n\"\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \"cf001\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py':$Run CPU layerwise benchmark on wrx90B\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \"cf001\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py'\nCommand exited with code 0.\n\nCommand output:\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 99 | |\n[line removed by the dashboard scrubber]\nL5 (global=True): dequant=1.01s, 16x3000 compute=28.62s\nL6 (global=False): dequant=0.91s, 16x3000 compute=50.78s\nTotal 2 layers: 81.43s -> est 60 layers (10 glob + 50 slid) = 2452.0s\nterminalJ&\n$run CPU layerwise benchmark on wrx90R\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \"cf001\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py'\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 99 | |\n[line removed by the dashboard scrubber]\nL5 (global=True): dequant=1.01s, 16x3000 compute=28.62s\nL6 (global=False): dequant=0.91s, 16x3000 compute=50.78s\nTotal 2 layers: 81.43s -> est 60 layers (10 glob + 50 slid) = 2452.0s\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \"cf001\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/104/output.txt"},{"i":105,"kind":"raw","long":false,"text":":(bot-91e6c941-b302-44dc-a92b-a38167dfa0edB!\n\tsessionID\nInitial hypothesis: resource contention is the root cause. Examining the system status file reveals a long-running process (`cf001-p0`) monopolizing a critical resource (GPU 0) for an extended duration. This suggests the observed performance issues are likely due to resource starvation. The timing for the next task will provide further confirmation.\n\n\n2(bot-91e6c941-b302-44dc-a92b-a38167dfa0ed:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/package_t12.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read package_t12.py on wrx90\"}:"},{"i":106,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/package_t12.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read package_t12.py on wrx90\"}:\n^ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/package_t12.py'\nt\n8Created At: 2026-11-14T15:12:29-05:00\nCompleted At: 2026-11-14T15:12:31-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Turn 12 deterministic packager, bit-for-bit SHA256 rebuild verifier, check_adapter + train_size runner,\nand exact runner.py ingest validator for author gemini.\n\"\"\"\nimport hashlib\nimport json\nimport re\nimport shutil\nimport stat\nimport subprocess\nimport sys\nfrom pathlib import Path\n[... 381 lines cut ...]\n\nif __name__ == \"__main__\":\n print(\"package_t12 ready\")\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2^ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/package_t12.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/106/output.txt"},{"i":107,"kind":"raw","long":false,"text":":(bot-14083728-2076-4f73-a20d-0a3bd4aa2799B!\n\tsessionID\nInitial assessment: `package_t12.py` appears to be a robust validation script. It systematically checks critical components like data splitting, sensitive data handling, adapter integrity, training size, and ensures build consistency via SHA256 checksums and file size. The presence of a final \"READY\" signal suggests successful completion and verification of the build.\n\n\n2(bot-14083728-2076-4f73-a20d-0a3bd4aa2799:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_cpu_insurance.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_cpu_insurance.py on wrx90\"}:"},{"i":108,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_cpu_insurance.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read t12_cpu_insurance.py on wrx90\"}:\ndssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_cpu_insurance.py'\n~\n=Created At: 2026-11-14T15:12:39-05:00\nCompleted At: 2026-11-14T15:12:41-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python3\n\"\"\"Zero-GPU CPU insurance pre-test (`CUDA_VISIBLE_DEVICES=\"\"`), running ONLY while `gpu0.lock` is still held\nby an external batch. Exits within <1s at any layer boundary the instant `t12_gpu.log` logs `Acquired gpu0.lock`!\n\"\"\"\nimport json, os, pathlib, sys, time\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"\nimport torch\nimport torch.nn.functional as F\ntorch.set_num_threads(20)\n\nR = pathlib.Path(\"/home/keith/gemma-v2\")\nME = R / \"wsp31/authors/gemini\"\n[... 331 lines cut ...]\n\nif __name__ == \"__main__\":\n main()\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2dssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gemini/code/t12_cpu_insurance.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/108/output.txt"},{"i":109,"kind":"raw","long":false,"text":":(bot-b68496db-8164-47b3-8755-12951b6d286fB!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\n2(bot-b68496db-8164-47b3-8755-12951b6d286f:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/claude/NOTES.md; echo \\\"=== GPT NOTES ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read claude and gpt NOTES.md (data only)\"}:"},{"i":110,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/claude/NOTES.md; echo \\\"=== GPT NOTES ===\\\"; cat /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read claude and gpt NOTES.md (data only)\"}:\n(Read claude and gpt NOTES.md (data only)\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/claude/NOTES.md; echo \"=== GPT NOTES ===\"; cat /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md'\nw\n9Created At: 2026-11-14T15:12:54-05:00\nCompleted At: 2026-11-14T15:12:57-05:00\nCommand exited with code 0.\n\nCommand output:\n# Notes of author claude (rewritten end of turn 14, 14 Nov 2026, 3:30 PM ET)\n\n## Scored so far\n- Depth-gate / end-of-thought family (0007 to 0023): null or harmful. Never resubmit the parked ones.\n- Instruction vectors (always-on neuron per layer): 0031 +9.0 at the old budget (stage 2 +9.5, control +7.5), 0032 null.\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n- x008 read (`code/x_stats.py` with batch and arms changed): finished wrong 27 (0050) and 29 (0049) against 27, 23\n unedited. My rule for 0050 was \"24 or less = dose response\": it did not fall. The gains came from fewer budget-outs\n (16 and 14 against 20, 25) and fewer empty patches. The line \"more of the exactness vector\" is closed.\n- 0031, 0032, 0039, 0050 wait for sealed 300-task runs (bar +8). Nothing to do for them.\n[... 118 lines cut ...]\n\nNo second READY yet. Finish only this second slot if checks pass; otherwise retain only 0027. Do not submit a third entry. The generation panel was prepared but not run. Deadline 20:52 UTC; keep notes below 600 words.\n\nUpdated 2026-11-14T20:01:02.967619+00:00.\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/claude/NOTES.md; echo \"=== GPT NOTES ===\"; cat /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/110/output.txt"},{"i":111,"kind":"raw","long":false,"text":":(bot-022fe4e9-7f3e-4961-940f-c03642a8a66fB!\n\tsessionID\nBoth models encountered the same GPU-0 state in their runs, confirmed by examining the logs. This suggests a shared operational constraint causing this behavior. Further analysis is now directed toward understanding this consistent GPU state.\n\n\nThe CPU replay observed until 20:52 UTC means CPU resource sharing needs adjustment using appropriate thread settings to prevent resource starvation, confirmed by monitoring the CPU load. Reviewing runner rules, a critical title length constraint of 140 characters must be enforced and added assertions for record splitting. GPU 0's occupation necessitates CPU pre-tests, and the missing CPU/second-GPU path in vgen.py prevented served generation.\n\n\nInitial hypothesis: Fitting outcome labels caused memorization, confirmed by performance gains on fit tasks versus unseen tasks. This validates avoiding outcome label fitting. Analysis of model `0050` reveals gain from budget-out and empty patch reductions, while avoiding the increase in `finished_wrong` seen in model `0038`.\n\n[line removed by the dashboard scrubber]\n\n\nModel `0044` demonstrates generalization to non-fit tasks, having solved multiple unseen problems. The model's use of zero outcome labels, instead measuring prompt-induced stream shifts, suggests a novel approach to problem-solving. This unexpected generalization warrants further investigation into the strategies employed by model `0044` to achieve these results, particularly given its performance on unseen tasks.\n\n\n2(bot-022fe4e9-7f3e-4961-940f-c03642a8a66f:'\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'uptime; ps -eo pid,user,pcpu,pmem,comm --sort=-pcpu | head -n 10'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check CPU load on wrx90\"}:%"},{"i":112,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'uptime; ps -eo pid,user,pcpu,pmem,comm --sort=-pcpu | head -n 10'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check CPU load on wrx90\"}:%\n]ssh -o BatchMode=yes wrx90 'uptime; ps -eo pid,user,pcpu,pmem,comm --sort=-pcpu | head -n 10'\nCreated At: 2026-11-14T15:13:21-05:00\nCompleted At: 2026-11-14T15:13:23-05:00\nCommand exited with code 0.\n\nCommand output:\n 15:13:23 up 1 day, 21:16, 12 users, load average: 55.07, 42.07, 41.15\n PID USER %CPU %MEM COMMAND\n2941673 keith 1922 2.6 python\n2947694 keith 1141 2.6 python\n2925467 keith 1135 40.4 python\n2954096 keith 263 0.2 python\n2954262 root 200 0.0 python\n2057580 keith 164 2.9 VLLM::EngineCor\n2374353 keith 148 2.6 VLLM::EngineCor\n 3053 root 37.7 0.2 containerd\n2951197 keith 15.0 0.3 python\n]ssh -o BatchMode=yes wrx90 'uptime; ps -eo pid,user,pcpu,pmem,comm --sort=-pcpu | head -n 10'\n15:13:23 up 1 day, 21:16, 12 users, load average: 55.07, 42.07, 41.15\n[... 7 lines cut ...]\n2374353 keith 148 2.6 VLLM::EngineCor\n 3053 root 37.7 0.2 containerd\n2951197 keith 15.0 0.3 python\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\n*\npowershell2]ssh -o BatchMode=yes wrx90 'uptime; ps -eo pid,user,pcpu,pmem,comm --sort=-pcpu | head -n 10':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/112/output.txt"},{"i":113,"kind":"raw","long":true,"text":":(bot-e1860e20-fc12-470b-befc-33d586ad72d9B!\n\tsessionID\nThe high CPU load observed during the script's execution points to contention from other concurrently running Python processes. These processes are consuming a significant number of cores, exceeding the intended thread count setting, which explains the performance degradation. This suggests that optimizing the script in isolation is insufficient; overall system resource management is crucial.\n\n\nUsing a fixed number of threads will likely resolve the CPU contention; the current configuration is inefficient. Investigating performance differences between several specific tasks and associated data files is the next step to identify performance bottlenecks. Checking the cosine similarities, norms, and gate profiles within the saved statistics will inform optimization strategies.\n\n\nExamining the available tensor statistics, `t9_stats.pt` includes gate and shift data across multiple audit and pre-edit calls, while `t12_tri_stats.pt` contains gate data from pre, post-work, and pre-sub calls. The focus is now on identifying patterns in these tensors to refine the model's behavior. The similarity analysis and norms will be critical in this refinement.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-e1860e20-fc12-470b-befc-33d586ad72d9:O\n({\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Inspect fit-vs-unseen transfer of 0043, 0044, 0055, 0056 and geometric relationships of saved stats.\\\"\\\"\\\"\\nimport json\\nimport pathlib\\nimport torch\\nimport torch.nn.functional as F\\nfrom forensic_t15_x009 import load_safe_sets, analyze_arm\\n\\nR = pathlib.Path(\\\"/home/keith/gemma-v2\\\")\\nME = R / \\\"wsp31/authors/gemini\\\"\\nDATA = ME / \\\"code/data\\\"\\nBATCHES = R / \\\"results/wsp31/batches\\\"\\n\\n\\ndef eval_split(batch: str, arm: str, fit_iids: set[str], valid119: set[str]):\\n b_st = analyze_arm(BATCHES / batch / \\\"base\\\", valid119)\\n a_st = analyze_arm(BATCHES / batch / \\\"aa\\\", valid119)\\n e_st = analyze_arm(BATCHES / batch / arm, valid119)\\n for name, sub in [(\\\"FIT\\\", valid119 \\u0026 fit_iids), (\\\"UNSEEN\\\", valid119 - fit_iids), (\\\"ALL\\\", valid119)]:\\n n = len(sub)\\n if n == 0:\\n continue\\n es = sum(1 for i in sub if e_st[i][\\\"resolved\\\"])\\n bs = sum(1 for i in sub if b_st[i][\\\"resolved\\\"])\\n aas = sum(1 for i in sub if a_st[i][\\\"resolved\\\"])\\n ref = 0.5 * (bs + aas)\\n gain = es - ref\\n ewc = sum(1 for i in sub if e_st[i][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\")\\n rwc = 0.5 * (sum(1 for i in sub if b_st[i][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\") + sum(1 for i in sub if a_st[i][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\"))\\n ecut = sum(1 for i in sub if e_st[i][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\"))\\n rcut = 0.5 * (sum(1 for i in sub if b_st[i][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\")) + sum(1 for i in sub if a_st[i][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\")))\\n print(f\\\" {batch}/{arm} [{name:6s} N={n:3d}]: edit={es:2d} vs ref={ref:5.1f} (gain={gain:+5.1f}, per120={gain*120/n:+5.1f}) | WC: {ewc:2d} vs {rwc:4.1f} | CUT+EMP: {ecut:2d} vs {rcut:4.1f}\\\")\\n\\n\\ndef main():\\n _, _, valid119 = load_safe_sets()\\n t9 = torch.load(DATA / \\\"t9_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\n t12_tri = torch.load(DATA / \\\"t12_tri_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\n t12_mk = torch.load(DATA / \\\"t12_mk_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\n\\n fit_t9 = {x[\\\"iid\\\"] for x in t9[\\\"fit_calls\\\"]}\\n fit_tri = {x[\\\"iid\\\"] for x in t12_tri[\\\"fit_calls\\\"]}\\n fit_mk = {x[\\\"iid\\\"] for x in t12_mk[\\\"fit_calls\\\"]}\\n\\n print(\\\"=== Fit vs Strictly Unseen Non-Fit Task Transfer ===\\\")\\n eval_split(\\\"x006\\\", \\\"e0043\\\", fit_t9, valid119)\\n eval_split(\\\"x006\\\", \\\"e0044\\\", fit_t9, valid119)\\n print(\\\"-\\\" * 95)\\n eval_split(\\\"x009\\\", \\\"e0055\\\", fit_mk, valid119)\\n eval_split(\\\"x009\\\", \\\"e0056\\\", fit_tri, valid119)\\n\\n print(\\\"\\\\n=== Layerwise Cosines \\u0026 Norms between t9\n[... 2921 characters cut ...]"},{"i":114,"kind":"raw","long":true,"text":"({\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Inspect fit-vs-unseen transfer of 0043, 0044, 0055, 0056 and geometric relationships of saved stats.\\\"\\\"\\\"\\nimport json\\nimport pathlib\\nimport torch\\nimport torch.nn.functional as F\\nfrom forensic_t15_x009 import load_safe_sets, analyze_arm\\n\\nR = pathlib.Path(\\\"/home/keith/gemma-v2\\\")\\nME = R / \\\"wsp31/authors/gemini\\\"\\nDATA = ME / \\\"code/data\\\"\\nBATCHES = R / \\\"results/wsp31/batches\\\"\\n\\n\\ndef eval_split(batch: str, arm: str, fit_iids: set[str], valid119: set[str]):\\n b_st = analyze_arm(BATCHES / batch / \\\"base\\\", valid119)\\n a_st = analyze_arm(BATCHES / batch / \\\"aa\\\", valid119)\\n e_st = analyze_arm(BATCHES / batch / arm, valid119)\\n for name, sub in [(\\\"FIT\\\", valid119 \\u0026 fit_iids), (\\\"UNSEEN\\\", valid119 - fit_iids), (\\\"ALL\\\", valid119)]:\\n n = len(sub)\\n if n == 0:\\n continue\\n es = sum(1 for i in sub if e_st[i][\\\"resolved\\\"])\\n bs = sum(1 for i in sub if b_st[i][\\\"resolved\\\"])\\n aas = sum(1 for i in sub if a_st[i][\\\"resolved\\\"])\\n ref = 0.5 * (bs + aas)\\n gain = es - ref\\n ewc = sum(1 for i in sub if e_st[i][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\")\\n rwc = 0.5 * (sum(1 for i in sub if b_st[i][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\") + sum(1 for i in sub if a_st[i][\\\"cat\\\"] == \\\"WRONG_CLEAN\\\"))\\n ecut = sum(1 for i in sub if e_st[i][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\"))\\n rcut = 0.5 * (sum(1 for i in sub if b_st[i][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\")) + sum(1 for i in sub if a_st[i][\\\"cat\\\"] in (\\\"CUTOFF_DIFF\\\", \\\"EMPTY_LIMIT\\\")))\\n print(f\\\" {batch}/{arm} [{name:6s} N={n:3d}]: edit={es:2d} vs ref={ref:5.1f} (gain={gain:+5.1f}, per120={gain*120/n:+5.1f}) | WC: {ewc:2d} vs {rwc:4.1f} | CUT+EMP: {ecut:2d} vs {rcut:4.1f}\\\")\\n\\n\\ndef main():\\n _, _, valid119 = load_safe_sets()\\n t9 = torch.load(DATA / \\\"t9_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\n t12_tri = torch.load(DATA / \\\"t12_tri_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\n t12_mk = torch.load(DATA / \\\"t12_mk_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\n\\n fit_t9 = {x[\\\"iid\\\"] for x in t9[\\\"fit_calls\\\"]}\\n fit_tri = {x[\\\"iid\\\"] for x in t12_tri[\\\"fit_calls\\\"]}\\n fit_mk = {x[\\\"iid\\\"] for x in t12_mk[\\\"fit_calls\\\"]}\\n\\n print(\\\"=== Fit vs Strictly Unseen Non-Fit Task Transfer ===\\\")\\n eval_split(\\\"x006\\\", \\\"e0043\\\", fit_t9, valid119)\\n eval_split(\\\"x006\\\", \\\"e0044\\\", fit_t9, valid119)\\n print(\\\"-\\\" * 95)\\n eval_split(\\\"x009\\\", \\\"e0055\\\", fit_mk, valid119)\\n eval_split(\\\"x009\\\", \\\"e0056\\\", fit_tri, valid119)\\n\\n print(\\\"\\\\n=== Layerwise Cosines \\u0026 Norms between t9_stats and t12_tri_stats Shifts ===\\\")\\n s_aud_all = t9[\\\"shifts\\\"][\\\"audit_all\\\"][\\\"mu\\\"].double()\\n s_aud_post9 = t9[\\\"shifts\\\"][\\\"audit_post\\\"][\\\"mu\\\"].double()\\n s_pre9 = t9[\\\"shifts\\\"][\\\"pre_only\\\"][\\\"mu\\\"].double()\\n s_foc12 = t12_tri[\\\"shifts\\\"][\\\"focus_all\\\"][\\\"mu\\\"].double()\\n s_aud_post12 = t12_tri[\\\"shifts\\\"][\\\"audit_post\\\"][\\\"mu\\\"].double()\\n s_veto12 = t12_tri[\\\"shifts\\\"][\\\"veto_submit\\\"][\\\"mu\\\"].double()\\n\\n for band_name, ls in [(\\\"L05-19\\\", range(5, 20)), (\\\"L20-39\\\", range(20, 40)), (\\\"L40-58\\\", range(40, 59))]:\\n def mcos(A, B):\\n cs = [float(F.cosine_similarity(A[l], B[l], dim=0)) for l in ls]\\n return sum(cs) / len(cs)\\n print(f\\\" {band_name}: cos(t9_aud_all, t9_aud_post)={mcos(s_aud_all, s_aud_post9):+.3f} | \\\"\\n f\\\"cos(t9_aud_post, t12_veto)={mcos(s_aud_post9, s_veto12):+.3f} | \\\"\\n f\\\"cos(t9_aud_all, t12_focus)={mcos(s_aud_all, s_foc12):+.3f} | \\\"\\n f\\\"cos(t9_pre, t12_focus)={mcos(s_pre9, s_foc12):+.3f} | \\\"\\n f\\\"cos(t9_aud_post, t12_aud_post)={mcos(s_aud_post9, s_aud_post12):+.3f}\\\")\\n\\n print(\\\"\\\\n=== Split-half cos_cum \\u0026 incremental rho comparison (t9 vs t12_tri) ===\\\")\\n for nm, sh in [\\n (\\\"t9.audit_all\\\", t9[\\\"shifts\\\"][\\\"audit_all\n[... 2330 characters cut ...]"},{"i":115,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\audit_stats_and_transfer.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run audit_stats_and_transfer.py on wrx90\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-115\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-115.log\"\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\audit_stats_and_transfer.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py':(Run audit_stats_and_transfer.py on wrx90B\n(Run audit_stats_and_transfer.py on wrx90\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\audit_stats_and_transfer.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py'\nCommand exited with code 0.\n\nCommand output:\n=== Fit vs Strictly Unseen Non-Fit Task Transfer ===\n x006/e0043 [FIT N= 32]: edit=21 vs ref= 21.0 (gain= +0.0, per120= +0.0) | WC: 7 vs 6.0 | CUT+EMP: 4 vs 4.5\n x006/e0043 [UNSEEN N= 87]: edit=58 vs ref= 55.5 (gain= +2.5, per120= +3.4) | WC: 20 vs 18.0 | CUT+EMP: 9 vs 13.0\n x006/e0043 [ALL N=119]: edit=79 vs ref= 76.5 (gain= +2.5, per120= +2.5) | WC: 27 vs 24.0 | CUT+EMP: 13 vs 17.5\n x006/e0044 [FIT N= 32]: edit=21 vs ref= 21.0 (gain= +0.0, per120= +0.0) | WC: 8 vs 6.0 | CUT+EMP: 3 vs 4.5\n x006/e0044 [UNSEEN N= 87]: edit=61 vs ref= 55.5 (gain= +5.5, per120= +7.6) | WC: 16 vs 18.0 | CUT+EMP: 10 vs 13.0\n x006/e0044 [ALL N=119]: edit=82 vs ref= 76.5 (gain= +5.5, per120= +5.5) | WC: 24 vs 24.0 | CUT+EMP: 13 vs 17.5\n-----------------------------------------------------------------------------------------------\n x009/e0055 [FIT N= 17]: edit=11 vs ref= 10.0 (gain= +1.0, per120= +7.1) | WC: 5 vs 3.0 | CUT+EMP: 1 vs 4.0\n x009/e0055 [UNSEEN N=102]: edit=67 vs ref= 71.5 (gain= -4.5, per120= -5.3) | WC: 34 vs 20.0 | CUT+EMP: 1 vs 10.5\n x009/e0055 [ALL N=119]: edit=78 vs ref= 81.5 (gain= -3.5, per120= -3.5) | WC: 39 vs 23.0 | CUT+EMP: 2 vs 14.5\n[... 60 lines cut ...]\n t9.post_thought : AUC_L20-58=0.848 | abar_med=1.272 | aneg_med=0.0617 (ratio=20.6x)\n t12.thought_quad : AUC_L20-58=0.959 | abar_med=3.740 | aneg_med=0.2253 (ratio=16.6x)\n t12.post_thought : AUC_L20-58=0.967 | abar_med=3.057 | aneg_med=0.0238 (ratio=128.7x)\n t12.submit_veto : AUC_L20-58=0.935 | abar_med=3.909 | aneg_med=0.0667 (ratio=58.6x)\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\audit_stats_and_transfer.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/audit_stats_and_transfer.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/115/output.txt"},{"i":116,"kind":"raw","long":true,"text":"[Message] timestamp=2026-11-14T20:13:35Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-104 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-104\" finished with result:\nCommand exited with code 0.\n\nCommand output:\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 99 | |\n[line removed by the dashboard scrubber]\nL5 (global=True): dequant=1.01s, 16x3000 compute=28.62s\nL6 (global=False): dequant=0.91s, 16x3000 compute=50.78s\nTotal 2 layers: 81.43s -> est 60 layers (10 glob + 50 slid) = 2452.0s\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-104.log\n-Run CPU layerwise benchmark on wrx90 finishedR\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\bench_layerwise_cpu.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; grep \"cf001\" $R/wsp31/queue/STATUS.md; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/bench_layerwise_cpu.py'\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 99 | |\n[line removed by the dashboard scrubber]\nL5 (global=True): dequant=1.01s, 16x3000 compute=28.62s\nL6 (global=False): dequant=0.91s, 16x3000 compute=50.78s\nTotal 2 layers: 81.43s -> est 60 layers (10 glob + 50 slid) = 2452.0s\n[... 11 lines cut ...]\n| cf001 | 0031+0015+0044 | - | open | | p0:running@0 p1:running@box |\n| cf001-p0 | 0031+0015+0044 | 0 | running | 99 | |\n[line removed by the dashboard scrubber]\nL5 (global=True): dequant=1.01s, 16x3000 compute=28.62s\nL6 (global=False): dequant=0.91s, 16x3000 compute=50.78s\nTotal 2 layers: 81.43s -> est 60 layers (10 glob + 50 slid) = 2452.0s\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-104.log"},{"i":117,"kind":"raw","long":false,"text":":(bot-a9c1680a-9200-41d7-b368-82d2ddfc4950B!\n\tsessionID\nThe timing breakdown reveals dequantization accounts for a significant portion of CPU time, with each layer taking roughly a second. This suggests that the dequantization process itself, when parallelized across layers, contributes to the overall speedup.\n\n\nThe performance discrepancy between the two tests is substantial, especially considering the different hardware. Examining the `attention()` function in the relevant script, it seems that there's an inefficient implementation involving explicit loops within `einsum` operations on floating-point tensors, which indicates this is the performance bottleneck. A shift to a more optimized attention mechanism, like scaled dot-product attention, could significantly reduce the processing time, potentially allowing multiple arms (base, edit, control) to run concurrently within a reasonable timeframe.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-a9c1680a-9200-41d7-b368-82d2ddfc4950:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/tools/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"List tools directory on wrx90\"}:"},{"i":118,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/tools/'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"List tools directory on wrx90\"}:\nEssh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/tools/'\ng\n2Created At: 2026-11-14T15:14:31-05:00\nCompleted At: 2026-11-14T15:14:33-05:00\nCommand exited with code 0.\n\nCommand output:\ntotal 864\ndrwxrwxr-x 10 keith keith 4096 Nov 14 13:09 .\ndrwxrwxr-x 18 keith keith 4096 Nov 14 13:33 ..\n-rw-r--r-- 1 keith keith 9736 Nov 12 19:41 ARCH.md\n-rw-r--r-- 1 keith keith 68439 Nov 13 20:50 REPORT.md\n-rw-r--r-- 1 keith keith 28053 Nov 13 15:51 TOOLS.md\ndrwxrwxr-x 2 keith keith 4096 Nov 14 12:27 __pycache__\ndrwxrwxr-x 13 keith keith 4096 Nov 13 01:07 adapters\n-rwxr-xr-x 1 keith keith 3285 Nov 12 19:23 adapters.py\n-rwxr-xr-x 1 keith keith 3612 Nov 13 14:34 armstats.py\n-rwxr-xr-x 1 keith keith 6085 Nov 12 19:49 atlas.py\n-rwxr-xr-x 1 keith keith 4065 Nov 12 19:49 av_contrast.py\n[... 213 lines cut ...]\n-rwxr-xr-x 1 keith keith 4005 Nov 12 19:59 wv_head.py\n-rwxr-xr-x 1 keith keith 3333 Nov 12 19:41 wv_lowrank.py\n-rwxr-xr-x 1 keith keith 3663 Nov 12 19:41 wv_neuron.py\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nz*\npowershell2Essh -o BatchMode=yes wrx90 'ls -la /home/keith/gemma-v2/wsp31/tools/':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/118/output.txt"},{"i":119,"kind":"raw","long":false,"text":":(bot-6330e578-664e-4166-be8f-1d88e1ebe907B!\n\tsessionID\nExamining the metric computation scripts (`delimprobe.py`, `closeprobe.py`, `replay.py`) is necessary to understand how the metrics are derived. The goal is to compute these metrics (closeprobe, delimprobe, and replay) concurrently within a single layer-by-layer CPU pass across unseen data. This integrated approach ensures efficiency.\n\n\n2(bot-6330e578-664e-4166-be8f-1d88e1ebe907:\n{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/closeprobe.py; echo \\\"=== DELIMPROBE ===\\\"; cat /home/keith/gemma-v2/wsp31/tools/delimprobe.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read closeprobe.py and delimprobe.py\"}:"},{"i":120,"kind":"raw","long":true,"text":"{\"CommandLine\":\"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/closeprobe.py; echo \\\"=== DELIMPROBE ===\\\"; cat /home/keith/gemma-v2/wsp31/tools/delimprobe.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Read closeprobe.py and delimprobe.py\"}:\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/closeprobe.py; echo \"=== DELIMPROBE ===\"; cat /home/keith/gemma-v2/wsp31/tools/delimprobe.py'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/120/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:14:52-05:00\nCompleted At: 2026-11-14T15:14:55-05:00\nCommand exited with code 0.\n\nCommand output:\n#!/usr/bin/env python\n\"\"\"closeprobe.py [--adapter DIR] [--champion current|DIR] [--probeset data/probe_calls_b001_full.jsonl] [--traces 40]\n[--per-trace 4] [--max-pos 6000] [--out FILE.json]: does this edit end thoughts sooner? Forward pass of this lane on\nGPU0 (no server; run under the gpu0 lock; about 5 s per call record and arm, the reference arm is cached).\n[line removed by the dashboard scrubber]\nset from `reqset.py --per-call`), never a context cut from a later stored prompt, where the harness has re-rendered\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nFor the reference model (unedited, or the champion) and for the edit it prints, per kind and per depth band (thought\n[... 436 lines cut ...]\n\n\nif __name__ == \"__main__\":\n main()\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/closeprobe.py; echo \"=== DELIMPROBE ===\"; cat /home/keith/gemma-v2/wsp31/tools/delimprobe.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/120/output.txt"},{"i":121,"kind":"raw","long":true,"text":"[Message] timestamp=2026-11-14T20:14:44Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-115 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-115\" finished with result:\nCommand exited with code 0.\n\nCommand output:\n=== Fit vs Strictly Unseen Non-Fit Task Transfer ===\n x006/e0043 [FIT N= 32]: edit=21 vs ref= 21.0 (gain= +0.0, per120= +0.0) | WC: 7 vs 6.0 | CUT+EMP: 4 vs 4.5\n x006/e0043 [UNSEEN N= 87]: edit=58 vs ref= 55.5 (gain= +2.5, per120= +3.4) | WC: 20 vs 18.0 | CUT+EMP: 9 vs 13.0\n x006/e0043 [ALL N=119]: edit=79 vs ref= 76.5 (gain= +2.5, per120= +2.5) | WC: 27 vs 24.0 | CUT+EMP: 13 vs 17.5\n x006/e0044 [FIT N= 32]: edit=21 vs ref= 21.0 (gain= +0.0, per120= +0.0) | WC: 8 vs 6.0 | CUT+EMP: 3 vs 4.5\n x006/e0044 [UNSEEN N= 87]: edit=61 vs ref= 55.5 (gain= +5.5, per120= +7.6) | WC: 16 vs 18.0 | CUT+EMP: 10 vs 13.0\n x006/e0044 [ALL N=119]: edit=82 vs ref= 76.5 (gain= +5.5, per120= +5.5) | WC: 24 vs 24.0 | CUT+EMP: 13 vs 17.5\n-----------------------------------------------------------------------------------------------\n x009/e0055 [FIT N= 17]: edit=11 vs ref= 10.0 (gain= +1.0, per120= +7.1) | WC: 5 vs 3.0 | CUT+EMP: 1 vs 4.0\n x009/e0055 [UNSEEN N=102]: edit=67 vs ref= 71.5 (gain= -4.5, per120= -5.3) | WC: 34 vs 20.0 | CUT+EMP: 1 vs 10.5\n x009/e0055 [ALL N=119]: edit=78 vs ref= 81.5 (gain= -3.5, per120= -3.5) | WC: 39 vs 23.0 | CUT+EMP: 2 vs 14.5\n x009/e0056 [FIT N= 35]: edit=21 vs ref= 21.0 (gain= +0.0, per120= +0.0) | WC: 11 vs 10.0 | CUT+EMP: 3 vs 4.0\n x009/e0056 [UNSEEN N= 84]: edit=59 vs ref= 60.5 (gain= -1.5, per120= -2.1) | WC: 13 vs 13.0 | CUT+EMP: 12 vs 10.5\n x009/e0056 [ALL N=119]: edit=80 vs ref= 81.5 (gain= -1.5, per120= -1.5) | WC: 24 vs 23.0 | CUT+EMP: 15 vs 14.5\n\n=== Layerwise Cosines & Norms between t9_stats and t12_tri_stats Shifts ===\n[... 100 lines cut ...]\n t9.comp_thought_quad : AUC_L20-58=0.987 | abar_med=3.492 | aneg_med=0.0298 (ratio=117.0x)\n t9.pre_thought : AUC_L20-58=0.834 | abar_med=0.004 | aneg_med=0.0163 (ratio=0.2x)\n t9.post_thought : AUC_L20-58=0.848 | abar_med=1.272 | aneg_med=0.0617 (ratio=20.6x)\n t12.thought_quad : AUC_L20-58=0.959 | abar_med=3.740 | aneg_med=0.2253 (ratio=16.6x)\n t12.post_thought : AUC_L20-58=0.967 | abar_med=3.057 | aneg_med=0.0238 (ratio=128.7x)\n t12.submit_veto : AUC_L20-58=0.935 | abar_med=3.909 | aneg_med=0.0667 (ratio=58.6x)\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-115.log"},{"i":122,"kind":"raw","long":true,"text":":(bot-fc1e7624-0c84-45c0-a880-01b9f905d979B!\n\tsessionID\nIInitial observation: Significant discrepancy found in audit statistics for task-115, specifically with the x006/e0044 entry, marked as \"UNSEEN\". The count (N=87) seems highly irregular.\n\nFurther analysis is required to understand why this entry is marked as unseen while other entries, such as x006/e0043 (FIT, N=32), show expected edit/reference parity. The large difference in count between the two states immediately demands investigation.\n\n\n[line removed by the dashboard scrubber]\n\n\n[line removed by the dashboard scrubber]\n\n\nThe analysis reveals highly performant new Turn-12 components, notably `t9.comp_thought_quad`, `t12.post_thought`, and `t12.submit_veto`, showing significantly enhanced suppression and AUC metrics compared to their Turn-9 counterparts. Further investigation highlights the `t12.veto_submit` component, exhibiting superior cross-task reliability and orthogonality to `t9.audit_post`, suggesting its potential for substantial gains. The focus now shifts to how these components might synergistically address the identified issues in the x006/e0044 entry.\n\n\nThe superior performance of the new components suggests a strategic shift toward incorporating veto mechanisms during the pre-submission phase to improve reliability. Initial exploration into the git diff and test results before submission is crucial to address any discrepancies or untested changes. The previous success with a submit veto mechanism (`j_2`) in a separate case reinforces the potential of this approach to reduce test failures and enhance overall robustness.\n\n\n[line removed by the dashboard scrubber]\n[... 42 lines cut ...]\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-fc1e7624-0c84-45c0-a880-01b9f905d979:\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\inspect_all_data_assets.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_all_data_assets.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_all_data_assets.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect all .pt data assets on wrx90\"}Z"},{"i":123,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n@C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_all_data_assets.py\n#!/usr/bin/env python3\n\"\"\"Inspect all detailed diagnostics inside code/data/*.pt to see every exact subspace we can compose on CPU.\"\"\"\nimport json\nimport pathlib\nimport torch\nimport torch.nn.functional as F\n\nR = pathlib.Path(\"/home/keith/gemma-v2\")\nDATA = R / \"wsp31/authors/gemini/code/data\"\n\n\ndef main():\n mk = torch.load(DATA / \"t12_mk_stats.pt\", map_location=\"cpu\", weights_only=False)\n tri = torch.load(DATA / \"t12_tri_stats.pt\", map_location=\"cpu\", weights_only=False)\n t9 = torch.load(DATA / \"t9_stats.pt\", map_location=\"cpu\", weights_only=False)\n g1 = torch.load(DATA / \"gemini_directions.pt\", map_location=\"cpu\", weights_only=False)\n gt5 = torch.load(DATA / \"gemini_t5_directions.pt\", map_location=\"cpu\", weights_only=False)\n\n[... 141 lines cut ...]\n.\n* sample_f1 = g1[\"f1_dirs\"][\"30.o_proj\"]\n[line removed by the dashboard scrubber]\nU\nQ print(\" gt5.summary['ortho_damp_r2']:\", gt5[\"summary\"].get(\"ortho_damp_r2\"))\nQ\nM print(\" gt5.summary['commit_gate']:\", gt5[\"summary\"].get(\"commit_gate\"))\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/123/output.txt"},{"i":124,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -o BatchMode=yes C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\inspect_all_data_assets.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_all_data_assets.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_all_data_assets.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect all .pt data assets on wrx90\"}2\nscp -o BatchMode=yes C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_all_data_assets.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_all_data_assets.py; ssh -o BatchMode=yes wrx90 '. /home/keith/gemma-v2/env.sh; $PY /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_all_data_assets.py'\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/124/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:16:27-05:00\nCompleted At: 2026-11-14T15:16:34-05:00\nCommand exited with code 0.\n\nCommand output:\n=== 1. t12_mk_stats.pt per-layer OOF r2 & beta_oof & rel_fro ===\n o_proj GLOBAL (9 layers): mean r2_oof=+0.0406 (pos=9/9), mean beta=0.208\n o_proj SLID (45 layers): mean r2_oof=+0.0211 (pos=45/45), mean beta=0.184\n down_proj GLOBAL (9 layers): mean r2_oof=+0.0177 (pos=9/9), mean beta=0.129\n down_proj SLID (45 layers): mean r2_oof=+0.0230 (pos=42/45), mean beta=0.161\n L05(GLOB): o[r2=+0.113, b=0.409, rel=0.14%, pres=0.3800] | d[r2=+0.035, b=0.163, rel=0.01%, pres=1.2976]\n L06(slid): o[r2=+0.098, b=0.379, rel=0.14%, pres=0.5420] | d[r2=+0.119, b=0.351, rel=0.06%, pres=0.6016]\n L07(slid): o[r2=+0.081, b=0.365, rel=0.10%, pres=0.5654] | d[r2=+0.160, b=0.561, rel=0.05%, pres=0.2768]\n L08(slid): o[r2=+0.062, b=0.297, rel=0.06%, pres=0.6082] | d[r2=+0.118, b=0.498, rel=0.03%, pres=0.3607]\n L09(slid): o[r2=+0.050, b=0.319, rel=0.07%, pres=0.4968] | d[r2=+0.069, b=0.468, rel=0.03%, pres=0.3627]\n[... 75 lines cut ...]\n g1.f1_heldout_auc: {'o_proj': 0.9992, 'down_proj': 0.9898}\n[line removed by the dashboard scrubber]\n gt5.summary['ortho_damp_r2']: {'heldout_auc': {'attn_raw': 0.8229, 'mlp_raw': 0.8646, 'mlp_in': 0.9757, 'attn_in': 0.8594}, 'max_abs_cos_with_close_r4': 1.0408340855860843e-16}\n gt5.summary['commit_gate']: {'layers': [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59], 'auc_vs_early': 0.675, 'auc_vs_post': 0.531, 'auc_vs_other': 0.9472, 'post_norm_cos_chk': 0.9496, 'mean_act_pos_late_pre': 0.4651, 'mean_act_neg_early_pre': 0.0157, 'mean_act_neg_post_edit': 0.0357, 'mean_act_neg_other': 0.00235, 'min_act_anywhere': 0.0, 'per_layer': {32: {'auc_early': 0.9, 'auc_post': 0.6, 'auc_other': 0.9535, 'post_norm_cos_chk': 0.9968, 'chk': {'pos_late_pre': {'n': 5, 'mean_z': -1.17, 'min_act': 7e-06, 'mean_act': 0.2425, 'fire_gt_0p25': 0.2}, 'neg_early_pre': {'n': 4, 'mean_z': -4.35, 'min_act': 0.0, 'mean_act': 0.0007, 'fire_gt_0p25': 0.0}, 'neg_post_edit': {'n': 3, 'mean_z': -2.03, 'min_act': 0.000209, 'mean_act': 0.0124, 'fire_gt_0p25': 0.0}, 'neg_arg': {'n': 23, 'mean_z': -7.32, 'min_act': 0.0, 'mean_act': 0.07, 'fire_gt_0p25': 0.0435}, 'neg_other': {'n': 142, 'mean_z': -10.94, 'min_act': 0.0, 'mean_act': 0.0029, 'fire_gt_0p25': 0.0}, 'mid_pre_6': {'n': 1, 'mean_z': -3.6, 'min_act': 0.000752, 'mean_act': 0.0008, 'fire_gt_0p25': 0.0}}}, 33: {'auc_early': 0.8, 'auc_post': 0.5333, 'auc_other': 0.9465, 'post_norm_cos_chk': 0.9971, 'chk': {'pos_late_pre': {'n': 5, 'mean_z': -1.39, 'min_act': 0.0, 'mean_act': 0.3591, 'fire_gt_0p25': 0.2}, 'neg_early_pre': {'n': 4, 'mean_z': -4.03, 'min_act': 1e-06, 'mean_act': 0.0014, 'fire_gt_0p25': 0.0}, 'neg_post_edit': {'n': 3, 'mean_z': -1.91, 'min_act': 0.000544, 'mean_act': 0.0134, 'fire_gt_0p25': 0.0}, 'neg_arg': {'n': 23, 'mean_z': -6.98, 'min_act': 0.0, 'mean_act': 0.0401, 'fire_gt_0p25': 0.0435}, 'ne\n[... 19079 characters cut ...]"},{"i":125,"kind":"raw","long":true,"text":":(bot-bc63e0b5-a7a4-4afc-a474-f11b2d219cecB!\n\tsessionID\nosH4aoiXObOFytMP6oaekAQb$82f18b21-3889-46a4-aaba-36510f202906\n:(bot-bc63e0b5-a7a4-4afc-a474-f11b2d219cecB!\n\tsessionID\n\n1. **Task Overview**\n - **Role & Turn**: Author `gemini` in the `wsp31` training-free weight-editing programme for `gemma-4-31b-it-qat-w4a16-ct` (Turn 15, started `2026-11-14T15:00:37-05:00`, 90-minute hard wall-clock deadline ~`16:30:37 EST`).\n - **Host & Workspace**: Remote host `wrx90` via `ssh -o BatchMode=yes wrx90 ''` and `scp`. Root `$R=/home/keith/gemma-v2`, Python `$PY=$R/tii-venv/bin/python`, tools `$T=$R/wsp31/tools`. Author directory (ONLY writable tree on `wrx90`): `/home/keith/gemma-v2/wsp31/authors/gemini/`. Local workspace: `C:\\Users\\Owner\\wsp31_loop\\work\\gemini`.\n - **Deliverables**:\n 1. Submit **ONE round of at most TWO new queue entries** under `$R/wsp31/authors/gemini/queue//` (`[a-z0-9][a-z0-9-]{2,39}`), finishing Entry 1 completely (`READY` file written last) before starting Entry 2.\n 2. Each entry requires: `edit/` (PEFT LoRA, `r <= 32`, `lora_alpha == 2*r`, bf16), `ctrl/` (matched control built by same code path, same matrices/ranks/norms), executable `build.sh` (deterministic bit-for-bit rebuild from `code/`), `record.md` (`title: `, then `## Hypothesis`, `## Exact recipe` with `base: champion generation 0` and `size: whole network % over matrices, largest matrix %` from `train_size.py`, `## Prediction (written before the run)` with `predicted_gain_120: to `), and empty `READY` file created last after checker + pre-tests pass.\n 3. At least one entry (ideally both) must be **training-sized**: `>= 0.3%` whole-network norm (`net_rel >= 0.003`) over `>= 100` matrices.\n 4. Rewrite `$R/wsp31/authors/gemini/NOTES.md` (**under 600 words**; keep updated as we go) and end the turn with a **five-line summary** of what was queued and why.\n\n2. **Progress**\n - **Required Reading Completed (Zero Redundant Re-reads Needed)**:\n - Read in full: `$R/wsp31/authors/BRIEF.md`, `authors/gemini/NOTES.md`, `authors/gemini/RESULTS.md`, `queue/CHAMPION.md` (still **Generation 0**, unedited model), `queue/STATUS.md`, `tii-wsp31-doc/research/wsp31/LEDGER.md` (through record `0060`), `ledger/0043`, `0044`, `0048`, `0050`, `0055`, `0056`, `0060`, `PRIOR_E4B.md`, `reports/2026-11-12-weight-editing-survey.md` (Sections A & C), `tools/TOOLS.md`, `tools/ARCH.md`, `interp/REPORT.md`, `tools/g31.py`, `tools/closeprobe.py`, `tools/delimprobe.py`, and peer notes (`authors/claude/NOTES.md`, `authors/gpt/NOTES.md`, treated strictly as data).\n - Inspected existing builders/packagers in `authors/gemini/code/`: `t9_build.py`, `t9_hold1.py`, `t12_build.py`, `t12_phase_a_g31.py`, `t12_fast_finish.py`, `t12_final_gpu_90s.py`, `t12_cpu_insurance.py`, `instant_package_now.py`, `package_t12.py`.\n[line removed by the dashboard scrubber]\n[... 180 lines cut ...]\n\"Ifile:///C:/Users/Owner/wsp31_loop/work/gemini/audit_stats_and_transfer.py*\nIfile:///C:/Users/Owner/wsp31_loop/work/gemini/audit_stats_and_transfer.py2\nHfile:///C:/Users/Owner/wsp31_loop/work/gemini/inspect_all_data_assets.py\n4type.googleapis.com/exa.cortex_pb.TrajectoryFileDiff\nHfile:///C:/Users/Owner/wsp31_loop/work/gemini/inspect_all_data_assets.py2\n\"Hfile:///C:/Users/Owner/wsp31_loop/work/gemini/inspect_all_data_assets.py*\nHfile:///C:/Users/Owner/wsp31_loop/work/gemini/inspect_all_data_assets.py2\nYou are author 'gemini' in the wsp31 weight-editing programme. This is turn 15. Your full instructions are in a brief on host wrx90. First run: ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md' and follow it exactly, working as author 'gemini' (your directory is /home/keith/gemma-v2/wsp31/authors/gemini/). The results of your last round, and every other author's entries and results, are in /home/keith/gemma-v2/wsp31/authors/gemini/RESULTS.md on wrx90: read it before you decide anything. This t\n[... 378 characters cut ...]"},{"i":126,"kind":"raw","long":false,"text":":(bot-14d58f7b-928b-46f7-91e7-32a7a45197f7B!\n\tsessionID\nReviewing the progress, all required preliminary steps are complete, with ample time remaining in the turn. Now, shifting focus to strategic planning based on the gathered information. This enables a targeted approach in the upcoming turn.\n\n\nInspecting the project files reveals the structure of build and packaging scripts, which informs the examination of statistical data files and unseen probe sets. This confirms the reuse of critical helper functions across build and packaging processes, ensuring consistency. The next step is building and testing the core code, and then running the pre-test battery.\n\n\n2(bot-14d58f7b-928b-46f7-91e7-32a7a45197f7:\n{\"CommandLine\":\"Get-ChildItem -Path C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\",\"WaitMsBeforeAsync\":5000,\"toolSummary\":\"List local workspace files\"}:\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Verify data assets and unseen probes\"}Z"},{"i":127,"kind":"raw","long":true,"text":"{\"CommandLine\":\"Get-ChildItem -Path C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\",\"WaitMsBeforeAsync\":5000,\"toolSummary\":\"List local workspace files\"}:\n9Get-ChildItem -Path C:\\Users\\Owner\\wsp31_loop\\work\\gemini\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/127/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:18:51-05:00\nCompleted At: 2026-11-14T15:18:52-05:00\nCommand exited with code 0.\n\nCommand output:\nDirectory: C:\\Users\\Owner\\wsp31_loop\\work\\gemini\nMode LastWriteTime Length Name\n---- ------------- ------ ----\n-a---- 11/13/2026 2:24 PM 13755 analyze_b002_b003.py\n-a---- 11/12/2026 10:56 PM 3986 analyze_probe_sets.py\n-a---- 11/14/2026 3:14 PM 4747 audit_stats_and_transfer.py\n-a---- 11/14/2026 7:39 AM 10656 audit_x2_deep.py\n-a---- 11/14/2026 7:38 AM 10121 audit_x2_regime.py\n-a---- 11/14/2026 12:23 PM 449 bench_g31_cpu.py\n-a---- 11/14/2026 3:12 PM 1741 bench_layerwise_cpu.py\n[... 168 lines cut ...]\n-a---- 11/12/2026 11:54 PM 1765 verify_runner_ingest.py\n-a---- 11/14/2026 3:11 PM 3842 wc_patterns_t15.py\n-a---- 11/12/2026 11:52 PM 32831 write_records_and_queue.py\n-a---- 11/13/2026 3:18 PM 27906 write_t5_entries.py\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nn*\npowershell29Get-ChildItem -Path C:\\Users\\Owner\\wsp31_loop\\work\\gemini:%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/127/output.txt"},{"i":128,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n@C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_assets_and_probes.py\n(\n[line removed by the dashboard scrubber]\nimport json\nfrom pathlib import Path\nimport torch\n\nR = Path(\"/home/keith/gemma-v2\")\nME = R / \"wsp31/authors/gemini\"\nDATA = ME / \"code/data\"\n\nt9 = torch.load(DATA / \"t9_stats.pt\", map_location=\"cpu\", weights_only=False)\ntri = torch.load(DATA / \"t12_tri_stats.pt\", map_location=\"cpu\", weights_only=False)\nmk = torch.load(DATA / \"t12_mk_stats.pt\", map_location=\"cpu\", weights_only=False)\n\n[line removed by the dashboard scrubber]\nfor k in [\"gates\", \"shifts\"]:\n if k in t9:\n[line removed by the dashboard scrubber]\n[... 176 lines cut ...]\nC\n? ids_len = len(r.get(\"ids\", r.get(\"input_ids\", [])))\n)\n% pts = r.get(\"points\", {})\npts_summary = {k: len(v) if isinstance(v, list) else v for k, v in pts.items()} if isinstance(pts, dict) else type(pts).__name__\n|\nx print(f\" inst={extract_inst(r)} call={r.get('call', r.get('call_idx'))} len={ids_len} pts={pts_summary}\")\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/128/output.txt"},{"i":129,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Verify data assets and unseen probes\"}2\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py'\nI\n!Created At: 2026-11-14T15:18:51-05:00\nCompleted At: 2026-11-14T15:18:58-05:00\nCommand exited with code 1.\n\nCommand output:\n[line removed by the dashboard scrubber]\n t9[gates]: {'thought_quad': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy']), 'comp_thought_quad': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy']), 'pre_thought': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy']), 'post_thought': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy'])}\n t9[shifts]: {'audit_all': ('dict', ['mu', 'mu_a', 'mu_b', 'cos_cum', 'n']), 'audit_post': ('dict', ['mu', 'mu_a', 'mu_b', 'cos_cum', 'n']), 'pre_only': ('dict', ['mu', 'mu_a', 'mu_b', 'cos_cum', 'n'])}\n sample t9 gate: {'w': torch.Size([60, 5376]), 'abar': torch.Size([60]), 'aneg': torch.Size([60]), 'auc_oof': torch.Size([60]), 'rmsy': torch.Size([60])}\n sample t9 shift: {'mu': torch.Size([60, 5376]), 'mu_a': torch.Size([60, 5376]), 'mu_b': torch.Size([60, 5376]), 'cos_cum': torch.Size([60]), 'n': 32}\n\n[line removed by the dashboard scrubber]\n tri[gates]: {'thought_quad': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy']), 'post_thought': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy']), 'submit_veto': ('dict', ['w', 'abar', 'aneg', 'auc_oof', 'rmsy'])}\n tri[shifts]: {'focus_all': ('dict', ['mu', 'mu_a', 'mu_b', 'cos_cum', 'n']), 'audit_post': ('dict', ['mu', 'mu_a', 'mu_b', 'cos_cum', 'n']), 'veto_submit': ('dict', ['mu', 'mu_a', 'mu_b', 'cos_cum', 'n'])}\n sample tri gate: {'w': torch.Size([60, 5376]), 'abar': torch.Size([60]), 'aneg': torch.Size([60]), 'auc_oof': torch.Size([60]), 'rmsy': torch.Size([60])}\n sample tri shift: {'mu': torch.Size([60, 5376]), 'mu_a': torch.Size([60, 5376]), 'mu_b': torch.Size([60, 5376]), 'cos_cum': torch.Size([60]), 'n': 36}\n\n[... 75 lines cut ...]\n File \"/home/keith/gemma-devagent-20261001/python/cpython-3.13.13-linux-x86_64-gnu/lib/python3.13/pathlib/_local.py\", line 537, in open\n return io.open(self, mode, buffering, encoding, errors, newline)\n ~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n[line removed by the dashboard scrubber]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/129/output.txt"},{"i":130,"kind":"raw","long":false,"text":":(bot-5032e6d3-5330-4b39-a18e-e7766fb36584B!\n\tsessionID\n2(bot-5032e6d3-5330-4b39-a18e-e7766fb36584:\nC{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t12_build.py\"}:\nE{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\package_t12.py\"}:y\nR{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\audit_stats_and_transfer.py\"}`"},{"i":131,"kind":"raw","long":true,"text":"C{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t12_build.py\"}:\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t12_build.py\nCreated At: 2026-11-14T15:19:12-05:00\nCompleted At: 2026-11-14T15:19:12-05:00\nShowing lines 1-550 of 550\n1: #!/usr/bin/env python3\n2: \"\"\"Deterministic CPU weight-edit builder for Turn 12 (author: gemini).\n3: \n4: Supports two training-sized closed-form architectures rebuilt bit-for-bit on CPU in <6s:\n5: 1. `tri_phase`: Capacity-regularized 3-neuron stateful GeGLU episode controller (`r=3`, 180 MLP matrices `0..59`)\n6: with focus/anti-rumination (`j_0`), post-edit spec-audit (`j_1`), and pre-submit diff-veto (`j_2`).\n[line removed by the dashboard scrubber]\n8: `o_proj` + `down_proj` across `5..58`) with SVD-spectrum-identical, syntax-nullspace-preserving orthogonal control.\n9: \"\"\"\n10: import argparse\n11: import json\n12: import pathlib\n13: import shutil\n14: import sys\n15: \n[... 532 lines cut ...]\n548: \n549: if __name__ == \"__main__\":\n550: main()\nA\n:file:///C:/Users/Owner/wsp31_loop/work/gemini/t12_build.py\n2z\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t12_build.py"},{"i":132,"kind":"raw","long":true,"text":"E{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\package_t12.py\"}2\n4C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\package_t12.py\nA\n?Created At: 2026-11-14T15:19:12-05:00\nCompleted At: 2026-11-14T15:19:12-05:00\nShowing lines 1-197 of 197\n1: #!/usr/bin/env python3\n2: \"\"\"Turn 12 deterministic packager, bit-for-bit SHA256 rebuild verifier, check_adapter + train_size runner,\n3: and exact runner.py ingest validator for author gemini.\n4: \"\"\"\n5: import hashlib\n6: import json\n7: import re\n8: import shutil\n9: import stat\n10: import subprocess\n11: import sys\n12: from pathlib import Path\n13: \n14: R = Path(\"/home/keith/gemma-v2\")\n[... 180 lines cut ...]\n195: \n196: if __name__ == \"__main__\":\n197: print(\"package_t12 ready\")\nC\n)={base_lp_close_mean:.4f} | \"\n1151: f\"cont logp()={base_lp_cont_mean:.4f}\", flush=True)\n1152: \n1153: TOK_SUBMIT, TOK_RUN = 15037, 4503\n1154: teach_sub_shift = []\n1155: for hr in held_ref:\n1156: if hr[\"rec\"][\"phase\"] == \"pre_sub\" and hr[\"col_idx\"]:\n1157: ci_p = hr[\"col_idx\"][0]\n1158: ds_b = float(hr[\"lp_base\"][ci_p, TOK_SUBMIT] - hr[\"lp_base\"][ci_p, TOK_RUN])\n1159: ds_t = float(hr[\"lp_teach\"][ci_p, TOK_SUBMIT] - hr[\"lp_teach\"][ci_p, TOK_RUN])\n1160: teach_sub_shift.append(ds_t - ds_b)\n1161: print(f\" [TEACHER GROUND TRUTH] pre_sub delta log(p_submit/p_run) mean={sum(teach_sub_shift)/max(1,len(teach_sub_shift)):+.4f}\", flush=True)\n1162: \n1163: def eval_adapter_full(adapter_dir: str, run_closeprobe: bool = True):\n[... 157 lines cut ...]\n1321: \n1322: \n1323: if __name__ == \"__main__\":\n1324: main()\nH\n@file:///C:/Users/Owner/wsp31_loop/work/gemini/t12_phase_a_g31.py\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\n8C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t12_phase_a_g31.py"},{"i":139,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n\"\"\"Verify unseen probe call disjointness and exact quiet_idx/layer_diag details.\"\"\"\nimport json\nfrom pathlib import Path\nimport torch\n\nR = Path(\"/home/keith/gemma-v2\")\nSETS = R / \"wsp31/queue/sets\"\nME = R / \"wsp31/authors/gemini\"\nDATA = ME / \"code/data\"\n\nt9 = torch.load(DATA / \"t9_stats.pt\", map_location=\"cpu\", weights_only=False)\ntri = torch.load(DATA / \"t12_tri_stats.pt\", map_location=\"cpu\", weights_only=False)\nmk = torch.load(DATA / \"t12_mk_stats.pt\", map_location=\"cpu\", weights_only=False)\n\nfit_t9 = {x[\"iid\"] for x in t9[\"fit_calls\"]}\nheld_t9 = {x[\"iid\"] for x in t9[\"held_calls\"]}\nfit_tri = {x[\"iid\"] for x in tri[\"fit_calls\"]}\nheld_tri = {x[\"iid\"] for x in tri[\"held_calls\"]}\nfit_mk = {x[\"iid\"] for x in mk[\"fit_calls\"]}\n[... 225 lines cut ...]\npts_summary = {k: len(v) if isinstance(v, list) else v for k, v in pts.items()} if isinstance(pts, dict) else type(pts).__name__\n|\nx print(f\" inst={extract_inst(r)} call={r.get('call', r.get('call_idx'))} len={ids_len} pts={pts_summary}\")\n|\nx pts_s = {k: len(v) if isinstance(v, list) else v for k, v in pts.items()} if isinstance(pts, dict) else None\nf\nb print(f\" iid={rec_iid(r)} call={r.get('call', r.get('ci'))} n={n_tok} pts={pts_s}\")\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/139/output.txt"},{"i":140,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Verify unseen probes and mk r2_oof\"}2\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py'\nU\n'Created At: 2026-11-14T15:19:42-05:00\nCompleted At: 2026-11-14T15:19:48-05:00\nCommand exited with code 0.\n\nCommand output:\nFit iids: t9=32, tri=36, mk=18, mk<=tri? True\nTotal union of fit iids (fit_t9 | fit_tri | fit_mk): 53\nsafe_s1=119, all_fit <= safe_s1? False, any in s2all? 0\n\n=== Quiet neuron max_abs / mean_abs check ===\nL00: t9_idx=[3729, 20335, 20849, 16094] max_abs=[27.5, 0.2383, 6.8438, 3.4844] | tri_idx=[8800, 11815, 4816, 18697] max_abs=[2.0312, 0.2754, 11.125, 7.8125]\nL10: t9_idx=[5962, 14753, 15762, 2423] max_abs=[24.25, 0.7812, 0.8711, 77.0] | tri_idx=[5962, 14753, 10495, 15762] max_abs=[28.875, 0.5938, 1.6562, 37.0]\nL25: t9_idx=[6473, 13594, 4381, 10717] max_abs=[4.0938, 2.2656, 2.8438, 2.5156] | tri_idx=[6473, 16300, 17316, 4381] max_abs=[4.2188, 2.1875, 2.6406, 3.6719]\nL40: t9_idx=[7243, 12870, 15683, 21374] max_abs=[8.75, 2.9688, 1.6953, 2.2031] | tri_idx=[7243, 10964, 19355, 12870] max_abs=[9.0625, 2.9688, 1.0078, 1.6328]\nL58: t9_idx=[12939, 14024, 2570, 10829] max_abs=[13.625, 1.5156, 1.4062, 8.6875] | tri_idx=[12939, 14024, 330, 14628] max_abs=[13.8125, 4.6875, 1.0625, 8.6875]\n\n=== mk layer_diag r2_oof summary ===\n[... 119 lines cut ...]\n iid=[task] call=None n=12000 pts=None\n iid=[task] call=None n=7178 pts=None\n iid=[task] call=None n=12000 pts=None\n iid=[task] call=None n=10217 pts=None\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_assets_and_probes.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_assets_and_probes.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/140/output.txt"},{"i":141,"kind":"raw","long":true,"text":":(bot-68b0d1df-ec64-4152-a4b7-c9b1c7375ce1B!\n\tsessionID\n)Initial hypothesis was that a caching issue might be the problem. However, the unexpected `False` result for `all_fit <= safe_s1` with specific identifiers needs further investigation. It appears this check is failing due to a specific copier instance failing the constraints.\n\n\nThe `all_fit <= safe_s1` check's failure stems from a copier instance. Reviewing the subtraction used in the `check_assets_and_probes.py` file to understand the `all_fit` task that is missing from the safe set. Specifically, confirm that subtraction logic and identifier set membership.\n\nAnalysis of probe data reveals that all records in `held26_calls2plus.jsonl` (179 records) and `held26_submit_calls.jsonl` (23 records) are unseen across all `t9`, `t12_tri`, and `t12_mk` statistics.\n\n\nThe analysis of `t12_mk_stats.pt` reveals significant overfitting in `down_proj` layers, particularly `L20-58`. The mean out-of-fold R-squared (`mean_r2_oof`) dramatically decreased while the preservation ratio (`mean_pres_ratio`) increased exponentially in these layers of `down_proj`. The `o_proj` layers do not have this issue. This discrepancy suggests the architecture of `down_proj` causes this overfit.\n\n\nThe `o_proj` attention layers effectively aggregate context with good generalization. The GeGLU-based MLP layers, particularly in the failing `down_proj` layers, provide non-linear gating. This gating mechanism, absent in the linear `down_proj`, seems crucial for filtering information, achieving significant suppression and AUC improvements.\n\n\nThe GeGLU MLP in `down_proj` enables non-linear state predicate computation, achieving significant suppression of non-matching phases. This contrasts with the attention layers that effectively aggregate context. Comparing two entries, one utilizes a pure 3-neuron stateful GeGLU MLP controller, while the other applies a focused attention mechanism with a broader reach. The controller entry achieves a higher AUC and better suppression than the attention-focused one.\n\n\nThe focus is on improving the model's performance by refining the gating mechanism. Specifically, upgrading a component by combining a cleaner gate with uncontaminated data and capacity regularization is necessary. Additionally, a new gate is being introduced to veto certain actions, ensuring that no projections fall into a \"premature-action\" vector, mitigating multi-test failures.\n[... 15 lines cut ...]\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-68b0d1df-ec64-4152-a4b7-c9b1c7375ce1:\n{\"Content\":\"\\\"\\\"\\\"Check edits.py rank padding, closeprobe/delimprobe APIs, fit task set check, and compact unseen probe selection.\\\"\\\"\\\"\\nimport json\\nfrom pathlib import Path\\nimport torch\\n\\nR = Path(\\\"/home/keith/gemma-v2\\\")\\nSETS = R / \\\"wsp31/queue/sets\\\"\\nT = R / \\\"wsp31/tools\\\"\\nME = R / \\\"wsp31/authors/gemini\\\"\\nDATA = ME / \\\"code/data\\\"\\n\\nt9 = torch.load(DATA / \\\"t9_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\ntri = torch.load(DATA / \\\"t12_tri_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\nmk = torch.load(DATA / \\\"t12_mk_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\nall_fit = {x[\\\"iid\\\"] for x in t9[\\\"fit_calls\\\"]} | {x[\\\"iid\\\"] for x in tri[\\\"fit_calls\\\"]} | {x[\\\"iid\\\"] for x in mk[\\\"fit_calls\\\"]}\\nall_internal_held = {x[\\\"iid\\\"] for x in t9[\\\"held_calls\\\"]} | {x[\\\"iid\\\"] for x in tri[\\\"held_calls\\\"]} | {x[\\\"iid\\\"] for x in mk[\\\"held_calls\\\"]}\\n\\ns2all = set()\\nfor p in SETS.glob(\\\"stage2*.txt\\\"):\\n s2all |= {x.strip() for x in p.read_text().splitlines() if x.strip()}\\ns1_v1 = {x.strip() for x in (SETS / \\\"stage1_ids.txt\\\").read_text().splitlines() if x.strip()}\\ns1_v2 = {x.strip() for x in (SETS / \\\"stage1_ids_v2.txt\\\").read_text().splitlines() if x.strip()}\\nprint(\\\"all_fit - s1_v2:\\\", all_fit - s1_v2)\\nprint(\\\"all_fit \\u003c= (s1_v1 | s1_v2)?\\\", all_fit \\u003c= (s1_v1 | s1_v2))\\nprint(\\\"all_fit \\u0026 s2all:\\\", all_fit \\u0026 s2all)\\nprint(\\\"all_internal_held \\u0026 s2all:\\\", all_in\n[... 1104 characters cut ...]"},{"i":142,"kind":"raw","long":true,"text":"{\"Content\":\"\\\"\\\"\\\"Check edits.py rank padding, closeprobe/delimprobe APIs, fit task set check, and compact unseen probe selection.\\\"\\\"\\\"\\nimport json\\nfrom pathlib import Path\\nimport torch\\n\\nR = Path(\\\"/home/keith/gemma-v2\\\")\\nSETS = R / \\\"wsp31/queue/sets\\\"\\nT = R / \\\"wsp31/tools\\\"\\nME = R / \\\"wsp31/authors/gemini\\\"\\nDATA = ME / \\\"code/data\\\"\\n\\nt9 = torch.load(DATA / \\\"t9_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\ntri = torch.load(DATA / \\\"t12_tri_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\nmk = torch.load(DATA / \\\"t12_mk_stats.pt\\\", map_location=\\\"cpu\\\", weights_only=False)\\nall_fit = {x[\\\"iid\\\"] for x in t9[\\\"fit_calls\\\"]} | {x[\\\"iid\\\"] for x in tri[\\\"fit_calls\\\"]} | {x[\\\"iid\\\"] for x in mk[\\\"fit_calls\\\"]}\\nall_internal_held = {x[\\\"iid\\\"] for x in t9[\\\"held_calls\\\"]} | {x[\\\"iid\\\"] for x in tri[\\\"held_calls\\\"]} | {x[\\\"iid\\\"] for x in mk[\\\"held_calls\\\"]}\\n\\ns2all = set()\\nfor p in SETS.glob(\\\"stage2*.txt\\\"):\\n s2all |= {x.strip() for x in p.read_text().splitlines() if x.strip()}\\ns1_v1 = {x.strip() for x in (SETS / \\\"stage1_ids.txt\\\").read_text().splitlines() if x.strip()}\\ns1_v2 = {x.strip() for x in (SETS / \\\"stage1_ids_v2.txt\\\").read_text().splitlines() if x.strip()}\\nprint(\\\"all_fit - s1_v2:\\\", all_fit - s1_v2)\\nprint(\\\"all_fit \\u003c= (s1_v1 | s1_v2)?\\\", all_fit \\u003c= (s1_v1 | s1_v2))\\nprint(\\\"all_fit \\u0026 s2all:\\\", all_fit \\u0026 s2all)\\nprint(\\\"all_internal_held \\u0026 s2all:\\\", all_internal_held \\u0026 s2all)\\n\\n# Inspect how closeprobe.py and delimprobe.py work, and how edits.py pads rank\\nprint(\\\"\\\\n=== edits.py save snippet ===\\\")\\ned_txt = (T / \\\"edits.py\\\").read_text().splitlines()\\nfor i, line in enumerate(ed_txt[120:230], start=121):\\n print(f\\\"{i:3d}: {line}\\\")\\n\\nprint(\\\"\\\\n=== closeprobe.py ===\\\" )\\nfor i, line in enumerate((T / \\\"closeprobe.py\\\").read_text().splitlines()[:95], start=1):\\n print(f\\\"{i:3d}: {line}\\\")\\n\\nprint(\\\"\\\\n=== delimprobe.py ===\\\")\\nfor i, line in enumerate((T / \\\"delimprobe.py\\\").read_text().splitlines()[:95], start=1):\\n print(f\\\"{i:3d}: {line}\\\")\\n\",\"Overwrite\":true,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\inspect_tools_api.py\"}:{\n:C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_tools_api.py\n\"\"\"Check edits.py rank padding, closeprobe/delimprobe APIs, fit task set check, and compact unseen probe selection.\"\"\"\nimport json\nfrom pathlib import Path\nimport torch\n\nR = Path(\"/home/keith/gemma-v2\")\nSETS = R / \"wsp31/queue/sets\"\nT = R / \"wsp31/tools\"\nME = R / \"wsp31/authors/gemini\"\nDATA = ME / \"code/data\"\n\nt9 = torch.load(DATA / \"t9_stats.pt\", map_location=\"cpu\", weights_only=False)\ntri = torch.load(DATA / \"t12_tri_stats.pt\", map_location=\"cpu\", weights_only=False)\nmk = torch.load(DATA / \"t12_mk_stats.pt\", map_location=\"cpu\", weights_only=False)\nall_fit = {x[\"iid\"] for x in t9[\"fit_calls\"]} | {x[\"iid\"] for x in tri[\"fit_calls\"]} | {x[\"iid\"] for x in mk[\"fit_calls\"]}\nall_internal_held = {x[\"iid\"] for x in t9[\"held_calls\"]} | {x[\"iid\"] for x in tri[\"held_calls\"]} | {x[\"iid\"] for x in mk[\"held_calls\"]}\n\ns2all = set()\n[... 60 lines cut ...]\n2ed_txt = (T / \"edits.py\").read_text().splitlines()\n9\n5for i, line in enumerate(ed_txt[120:230], start=121):\n[\nWfor i, line in enumerate((T / \"closeprobe.py\").read_text().splitlines()[:95], start=1):\n[\nWfor i, line in enumerate((T / \"delimprobe.py\").read_text().splitlines()[:95], start=1):\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/142/output.txt"},{"i":143,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\inspect_tools_api.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_tools_api.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_tools_api.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Inspect edits, closeprobe, delimprobe APIs\"}2\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_tools_api.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_tools_api.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_tools_api.py'\n*Inspect edits, closeprobe, delimprobe APIs\nOThe tool's output was truncated due to being too long. You can find the full output in a file at file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/143/output.txt.\n\nHere is a preview with the middle of the output truncated:\nCreated At: 2026-11-14T15:20:47-05:00\nCompleted At: 2026-11-14T15:20:53-05:00\nCommand exited with code 0.\n\nCommand output:\nall_fit - s1_v2: set()\nall_fit <= (s1_v1 | s1_v2)? True\nall_fit & s2all: set()\nall_internal_held & s2all: set()\n\n=== edits.py save snippet ===\n121: return self._file().get_tensor(f\"{g31.LM}layers.{l}.{name}{suffix}\").float()\n122: \n123: def embed(self, tok):\n[... 488 lines cut ...]\n 92: ap.add_argument(\"--traces\", type=int, default=40)\n 93: ap.add_argument(\"--max-pos\", type=int, default=6000)\n 94: ap.add_argument(\"--min-call\", type=int, default=1)\n 95: ap.add_argument(\"--arg-per-call\", type=int, default=8)\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\inspect_tools_api.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_tools_api.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/inspect_tools_api.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/143/output.txt"},{"i":144,"kind":"raw","long":false,"text":":(bot-bfcaff08-70b2-4977-b3cc-787dad3d2205B!\n\tsessionID\nReading the specified file lines to understand the `save()` and `closeprobe` functions within `edits.py`. These functions are crucial for writing and finalizing changes. Examination should reveal how data is persistently stored and probes are handled in this process.\n\n\n2(bot-bfcaff08-70b2-4977-b3cc-787dad3d2205:\n{\"EndLine\":230,\"Path\":\"C:\\\\Users\\\\Owner\\\\.gemini\\\\antigravity-cli\\\\brain\\\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\\\.system_generated\\\\steps\\\\143\\\\output.txt\",\"StartLine\":90}:"},{"i":145,"kind":"raw","long":true,"text":"{\"EndLine\":230,\"Path\":\"C:\\\\Users\\\\Owner\\\\.gemini\\\\antigravity-cli\\\\brain\\\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\\\.system_generated\\\\steps\\\\143\\\\output.txt\",\"StartLine\":90}:\nxC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\steps\\143\\output.txt\nJ\nGCreated At: 2026-11-14T15:21:03-05:00\nCompleted At: 2026-11-14T15:21:03-05:00\nShowing lines 90-230 of 315\n90: 199: us.append(d.reshape(o, 1))\n91: 200: vs.append(e)\n[line removed by the dashboard scrubber]\n93: 202: us.append(u)\n94: 203: vs.append(v)\n[line removed by the dashboard scrubber]\n96: 205: return out\n97: 206: \n98: 207: def delta(self, l, mod):\n99: 208: \"\"\"Dense dW for one module, fp32 [out, in] (before bf16 storage rounding).\"\"\"\n100: 209: u, v = self.factors()[(l, mod)]\n101: 210: return u @ v\n102: 211: \n103: 212: def ranks(self):\n[... 122 lines cut ...]\n226: 6: (between <|tool_call> (48) and (49)) it takes\n[line removed by the dashboard scrubber]\n228: 8: string here;\n229: 9: arg up to --arg-per-call other positions inside the tool call (evenly spaced): the agent wrote argument text;\n230: 10: tend the position before : the agent closed the call.\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/143/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nxC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\steps\\143\\output.txt Z("},{"i":146,"kind":"raw","long":false,"text":":(bot-01c580e8-c53f-4065-a8b3-ab7de2e16083B!\n\tsessionID\nAll 53 fit tasks are within one set and have no overlap with another. This suggests a potential partitioning issue or a need to re-evaluate how these tasks interact across the sets. Further investigation is required to understand why one set exclusively contains all tasks.\n\n\nThe `EditSet.save()` function appears to handle mixed-rank modules by padding them to a uniform adapter rank. A self-test with `check_adapter.py` will confirm this behavior.\n\nA single 60-layer CPU pass, using `closeprobe` and `delimprobe` directly within `t15_cpu_pretest.py` from `$T`, will compute `closeprobe.table` and `delimprobe.table` data. This approach allows for the efficient calculation of various metrics including KL divergence, top-1 flip rate, and tool-call shifts related to `submit_patch`.\n\n\nDirectly calibrating against adapters `0044`, `0055`, and `0056` offers a definitive comparison, bypassing speculation on metric correlations to performance deltas. The adapters themselves are accessible, either in the existing directory structure or easily rebuildable via available scripts, allowing for a precise evaluation. Evaluating additional reference arms on the CPU will incur minimal computational overhead.\n\n\nThe shared dequantization of the base matrices across arms is confirmed. Further investigation involves examining `o_proj` within `t12_mk_stats.pt` to understand its interactions with data from `t12.focus_all[l]` and `t9` components. A CPU geometry diagnostic will analyze neuron selection and calculate cosines and reliability metrics across different configurations.\n\n\n2(bot-01c580e8-c53f-4065-a8b3-ab7de2e16083:W\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check T15 geometry and unseen probes\"}Z"},{"i":147,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n+\"\"\"Fast 5-second CPU geometry & probe-length check for Turn 15 recipes.\"\"\"\nimport json\nfrom pathlib import Path\nimport sys\nimport torch\nimport torch.nn.functional as F\n\nR = Path(\"/home/keith/gemma-v2\")\nT = R / \"wsp31/tools\"\nME = R / \"wsp31/authors/gemini\"\nDATA = ME / \"code/data\"\nsys.path.insert(0, str(T))\nfrom edits import EditSet\nimport probeset\nimport delimprobe\n\nt9 = torch.load(DATA / \"t9_stats.pt\", map_location=\"cpu\", weights_only=False)\ntri = torch.load(DATA / \"t12_tri_stats.pt\", map_location=\"cpu\", weights_only=False)\nmk = torch.load(DATA / \"t12_mk_stats.pt\", map_location=\"cpu\", weights_only=False)\n[... 210 lines cut ...]\nV\nRsub_recs = probeset.load(str(ME / \"scratch/t12_probes/held26_submit_calls.jsonl\"))\n:\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n`\n\\ print(f\" {r['instance']:48s} call={r['call']:2d} n={r['n']:4d} pts={len(r['points'])}\")\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/147/output.txt"},{"i":148,"kind":"raw","long":false,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check T15 geometry and unseen probes\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-148\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-148.log\"\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py':$Check T15 geometry and unseen probesB\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py'\nterminalJ&\n$check T15 geometry and unseen probesR\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py'"},{"i":149,"kind":"raw","long":false,"text":":(bot-e73a3401-8ade-4029-ae3b-99f19736b9c8B!\n\tsessionID\nDrafting the Python script locally as a preliminary step, anticipating dependencies on the ongoing task. The previous task encountered an unexpected delay, the root cause was the presence of an unused variable, and I will be working on improving the build scripts.\n\n\n2(bot-e73a3401-8ade-4029-ae3b-99f19736b9c8:\n^{\"EndLine\":160,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t9_build.py\",\"StartLine\":1}:"},{"i":150,"kind":"raw","long":true,"text":"^{\"EndLine\":160,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t9_build.py\",\"StartLine\":1}:\n1C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t9_build.py\n2\n0Created At: 2026-11-14T15:22:06-05:00\nCompleted At: 2026-11-14T15:22:06-05:00\nShowing lines 1-160 of 346\n1: #!/usr/bin/env python3\n2: \"\"\"Deterministic CPU weight-edit builder for Turn 9 (author: gemini).\n3: \n4: Rebuilds both `edit/` and matched `ctrl/` adapters bit-for-bit on CPU from\n5: `/home/keith/gemma-v2/wsp31/authors/gemini/code/data/t9_stats.pt` without touching a GPU.\n6: \"\"\"\n7: import argparse\n8: import json\n9: import pathlib\n10: import shutil\n11: import sys\n12: \n13: import torch\n14: \n[... 143 lines cut ...]\n158: \n159: basis = [col_base, d_edit] + [v.double() for v in (extra_orth or [])]\n160: q_list = []\n@\n9file:///C:/Users/Owner/wsp31_loop/work/gemini/t9_build.py\n2w\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\n1C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t9_build.py"},{"i":151,"kind":"raw","long":false,"text":":(bot-87018eff-198e-4b98-9f7f-ebb97ac7392fB!\n\tsessionID\n2(bot-87018eff-198e-4b98-9f7f-ebb97ac7392f:\n`{\"EndLine\":346,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t9_build.py\",\"StartLine\":161}:\nh{\"EndLine\":90,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\finalize_t9_entries.py\",\"StartLine\":1}`"},{"i":152,"kind":"raw","long":true,"text":"`{\"EndLine\":346,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t9_build.py\",\"StartLine\":161}:\n1C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t9_build.py\n?\n=Created At: 2026-11-14T15:22:11-05:00\nCompleted At: 2026-11-14T15:22:12-05:00\nShowing lines 161-346 of 346\n161: for b in basis:\n162: v = b.clone()\n163: for q in q_list:\n164: v = v - (v @ q) * q\n165: nv = float(v.norm().item())\n166: if nv > 1e-10:\n167: q_list.append(v / nv)\n168: \n169: for q in q_list:\n170: cand = cand - (cand @ q) * q\n171: cand_u = cand / max(float(cand.norm().item()), 1e-12)\n172: d_ctrl = target_norm * cand_u\n173: return d_edit.float(), d_ctrl.float()\n174: \n[... 169 lines cut ...]\n344: \n345: if __name__ == \"__main__\":\n346: main()\nA\n9file:///C:/Users/Owner/wsp31_loop/work/gemini/t9_build.py\n2x\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\n1C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t9_build.py"},{"i":153,"kind":"raw","long":true,"text":"h{\"EndLine\":90,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\finalize_t9_entries.py\",\"StartLine\":1}2\n 0.02: 48/54; top 8: [(5, 0.1134, 0.38, 0.3367), (11, 0.1125, 0.402, 0.3354), (6, 0.0984, 0.542, 0.3073), (7, 0.0811, 0.565, 0.2759), (12, 0.0711, 0.554, 0.2597), (14, 0.0671, 0.44, 0.259), (17, 0.0687, 0.534, 0.2578), (13, 0.0642, 0.471, 0.2534)]\nmk o_proj L35-58 mean wl=0.0367 vs L05-19 mean wl=0.2501\n\n[line removed by the dashboard scrubber]\n [task] call= 1 n=2910 close=1 cont=2 delim=2\n [task] call=21 n=3005 close=1 cont=1 delim=2\n jsvine__pdfplumber.02ff4313.func_pm_remove_assign__1v9soh1j call= 2 n=3339 close=1 cont=1 delim=2\n [task] call=41 n=3359 close=1 cont=3 delim=0\n [task] call= 1 n=3436 close=1 cont=2 delim=2\n pallets__markupsafe.620c06c9.combine_file__7pv2r8sa call=10 n=3487 close=1 cont=4 delim=2\n[... 34 lines cut ...]\n [task] call=17 n=5546 pts=8\n [task] call=22 n=5566 pts=7\n [task] call=31 n=5622 pts=7\n mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm call=35 n=5727 pts=8\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/159/output.txt"},{"i":160,"kind":"raw","long":false,"text":"[Message] timestamp=2026-11-14T20:22:31Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-148 priority=MESSAGE_PRIORITY_LOW content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-148\" was canceled with result:\nTool execution was canceled\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-148.log\n1Check T15 geometry and unseen probes was canceled\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py'\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-148(\nR3\n1Check T15 geometry and unseen probes was canceledX\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\check_t15_geometry.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/check_t15_geometry.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Check T15 geometry and unseen probes\"}\"\nTask id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-148\" was canceled with result:\nTool execution was canceled\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-148.log"},{"i":161,"kind":"raw","long":true,"text":":(bot-34922de4-d16c-4952-83b0-bcef9d93f37dB!\n\tsessionID\nThe geometry check script confirms a clean mathematical relationship between the veto and focus vectors across all layers, specifically for mu, mu_a, and mu. The output strongly suggests the transformation is correct. This is the positive confirmation needed.\n\n\nSplit-half reliability improved slightly in specific layers after removing the `focus_all` projection, suggesting the transformation is beneficial. Joint selection of `quiet_idx` significantly reduced the worst-case `max_abs` value across all layers while maintaining mean activation. Analysis of out-of-task cross-validation scores revealed that early global-attention layers, which attend to the Problem Statement, exhibit the highest predictive power, indicating their critical role.\n\n\nThe high stream energy fraction along `focus_all` in specific layers suggests a significant bias in `o_proj`. Removing this bias through orthogonal projection should preserve context-conditional routing while eliminating the premature-action bias. This approach relies on exact linear algebra for stream-orthogonalization to the `focus_all` vector.\n\n\nThe debiasing strategy targets the removal of the residual stream component along the focus direction via a corrective orthogonal projection. This is achieved by adjusting the native projection matrix using a scaling factor derived from the inner product of the stream with a weighted focus direction, ensuring a zero inner product and thus, complete orthogonalization, after application. The approach hinges on a well-conditioned native update to the `o_proj` operation.\n\n\nThe orthogonal debiasing formula directly corrects the projection matrix by subtracting only the rank-1 component along the focus direction, avoiding distortion of other coordinates. This approach ensures exact orthogonalization in the residual stream. This method provides textbook-clean numerical linear algebra, preserving the orthogonal complement and guaranteeing the desired result. Now, creating `code/t15_build.py`.\n\n\nThe code generates and compares matched edit/control cases. Recipe 1, `pure_audit_veto_r3`, involves deterministic selection of quiet neuron triples minimizing the combined `max_mean_abs` and `max_peak_abs` across layers. The selected neurons' behaviors are carefully specified using gate and shift matrices.\n\n**Additional Notes:**\n[... 12 lines cut ...]\n[line removed by the dashboard scrubber]\n\nThe analysis considers two experimental entries: Entry 1 and Entry 2, designed as a matched pair to test distinct auditing mechanisms. Entry 1 focuses on a pure all-thought MLP-based specification audit. The two entries enable a controlled comparison of different edit strategies, with norm-matched parameters and matrix dimensions.\n\n\n2(bot-34922de4-d16c-4952-83b0-bcef9d93f37d:\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run t15_build.py selftest on wrx90\"}Z"},{"i":162,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py\n#!/usr/bin/env python3\n\"\"\"Deterministic CPU weight-edit builder for Turn 15 (author: gemini).\n\nSupports two training-sized closed-form architectures rebuilt bit-for-bit on CPU in <6s:\n1. `pure_audit_veto_r3`: Capacity-regularized 3-neuron stateful GeGLU MLP controller (`r=3`, 180 MLP matrices `0..59`)\n combining:\n - `j_0`: `t9.comp_thought_quad` gate (OOF AUC 0.987, 117x suppression) + pure `t9.audit_all` shift (zero P_FOCUS),\n - `j_1`: `t12.post_thought` gate (OOF AUC 0.967, 128.7x suppression) + uncontaminated `t9.audit_post` shift,\n - `j_2`: `t12.submit_veto` gate (OOF AUC 0.935, 58.6x suppression) + `focus_all`-orthogonalized `t12.veto_submit`.\n2. `hybrid_oproj_postveto_r6`: Strictly disjoint-matrix Attention + MLP hybrid (`r=6`, 230 matrices:\n 50 `o_proj` matrices in `5..54` + 180 MLP matrices in `0..59`):\n[line removed by the dashboard scrubber]\n exact post-layernorm stream-space `focus_all` debiasing and Empirical-Bayes `r2_oof` / preserve-ratio weighting\n (dropping noisy `down_proj` linear ridge completely).\n - MLP (`0..59`, 2 stateful neurons `j_1, j_2`): post-edit `t9.audit_post` + `focus_all`-orthogonalized `submit_veto`\n (zero pre-edit MLP intervention).\n\"\"\"\nimport argparse\n[... 1276 lines cut ...]\n) \"ctrl_changed\": re_ct[\"changed\"],\n7\n3 \"ctrl_net_rel\": round(re_ct[\"net_rel\"], 6),\n7\n3 \"ctrl_rel_max\": round(re_ct[\"rel_max\"], 6),\n_\n[ \"meta\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/162/output.txt"},{"i":163,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Run t15_build.py selftest on wrx90\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-163.log\"\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest':\"Run t15_build.py selftest on wrx90B\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\nCommand exited with code 1.\n\nCommand output:\nTraceback (most recent call last):\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 658, in \n main()\n ~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 618, in main\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={re1['rel_max']*100:.4f}%\")\n ~~~^^^^^^^^^^^\n[line removed by the dashboard scrubber]\nterminalJ$\n[... 9 lines cut ...]\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={re1['rel_max']*100:.4f}%\")\n ~~~^^^^^^^^^^^\n[line removed by the dashboard scrubber]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/163/output.txt"},{"i":164,"kind":"raw","long":false,"text":":(bot-bc8ff995-55c3-4ff7-bce3-f162572920cbB!\n\tsessionID\nInspecting the `bench_layerwise_cpu.py` script to understand the CPU layer-by-layer forward pattern. This information will be used to generate a corresponding test in `code/t15_cpu_pretest.py` that mimics the `g31` CPU execution. The goal is to create a test that can be compared against the performance results of `task-163`'s selftest.\n\n\n2(bot-bc8ff995-55c3-4ff7-bce3-f162572920cb:\nM{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\bench_layerwise_cpu.py\"}:"},{"i":165,"kind":"raw","long":true,"text":"M{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\bench_layerwise_cpu.py\"}:\n est 60 layers (10 glob + 50 slid) = {10*dq_s + 60*(dt/2):.1f}s\", flush=True)\nJ\nDfile:///C:/Users/Owner/wsp31_loop/work/gemini/bench_layerwise_cpu.py\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\n dense bf16 [out, in] replacement weight (full-rank edits)\n144: 139\t self.f = safe_open(os.path.join(model_dir, \"model.safetensors\"), framework=\"pt\", device=str(self.dev))\n145: 140\t g = self.f.get_tensor\n[line removed by the dashboard scrubber]\n147: 142\t self.final_norm = g(LM + \"norm.weight\")\n148: 143\t # vLLM: torch.tensor(hidden_size ** 0.5) registered as a buffer and cast to the model dtype\n149: 144\t self.normalizer = torch.tensor(self.arch.d ** 0.5).to(BF).to(self.dev)\n150: 145\t self.L = {}\n151: 146\t for l in (range(self.arch.n_layers) if layers is None else layers):\n152: 147\t p = f\"{LM}layers.{l}.\"\n153: 148\t d = {k: g(p + k + \".weight\") for k in (\"input_layernorm\", \"post_attention_layernorm\",\n[... 92 lines cut ...]\n246: 241\t x1, x2 = x[..., :h], x[..., h:]\n247: 242\t return torch.cat([x1 * cos - x2 * sin, x2 * cos + x1 * sin], dim=-1)\n248: 243\t\n249: 244\t def attention(self, q, k, v, window, budget=None):\n250: 245\t \"\"\"Causal (optionally sliding-window) GQA attention, softmax scale 1.0. q [N, H, d]; k, v [N, KV, d].\"\"\"\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/167/output.txt\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nxC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\steps\\167\\output.txt"},{"i":170,"kind":"raw","long":false,"text":"{\"Path\":\"C:\\\\Users\\\\Owner\\\\.gemini\\\\antigravity-cli\\\\brain\\\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\\\.system_generated\\\\tasks\\\\task-163.log\"}2\nvC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\tasks\\task-163.log\n[Created At: 2026-11-14T15:25:37-05:00\nCompleted At: 2026-11-14T15:25:37-05:00\nFile is empty\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-163.log2\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nvC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\tasks\\task-163.log"},{"i":171,"kind":"raw","long":false,"text":":(bot-1a7d05d6-2975-4f8e-a57a-0bc195cd80fdB!\n\tsessionID\nThe code snippet shows a clear application of `gelu_tanh` to a floating-point `gate` tensor, followed by a rounding operation to bfloat16 using `self._r`. This confirms the expected data type conversion within this specific part of the model. This `act` variable's role and data type are crucial to understand the overall numerical stability.\n\n\nThe `lin_preloaded` function's behavior, especially the dequantization of the weight `w` using `m.base_weight`, is central. This function, with the dequantized weights, mirrors the behavior of `g31.G31.forward`. The application of the linear transformation `F.linear` across multiple arms and sequences presents a potential optimization opportunity.\n\n\nThe current implementation streams approximately 950MB of weights from RAM per layer multiple times, leading to significant memory bandwidth usage. Combining the weights and performing a single large matrix multiplication could drastically reduce memory bandwidth by a factor of 56. Moreover, specific layers exhibit identical attention patterns across certain operations, suggesting an opportunity for further optimization and reuse.\n\n\n2(bot-1a7d05d6-2975-4f8e-a57a-0bc195cd80fd:\nL{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163\"}:"},{"i":172,"kind":"raw","long":true,"text":"L{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163\"}:\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163\nCreated At: 2026-11-14T15:25:52-05:00\nCompleted At: 2026-11-14T15:25:52-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163\nStatus: DONE\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-163.log\nLog output:\nTraceback (most recent call last):\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 658, in \n main()\n ~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 618, in main\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={re1['rel_max']*100:.4f}%\")\n ~~~^^^^^^^^^^^\n[line removed by the dashboard scrubber]\n\n[... 13 lines cut ...]\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={re1['rel_max']*100:.4f}%\")\n ~~~^^^^^^^^^^^\n[line removed by the dashboard scrubber]\n```2o\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/172/output.txt"},{"i":173,"kind":"raw","long":true,"text":"[Message] timestamp=2026-11-14T20:25:40Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-163\" finished with result:\nCommand exited with code 1.\n\nCommand output:\nTraceback (most recent call last):\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 658, in \n main()\n ~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 618, in main\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={re1['rel_max']*100:.4f}%\")\n ~~~^^^^^^^^^^^\n[line removed by the dashboard scrubber]\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-163.log\n+Run t15_build.py selftest on wrx90 finishedR\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\nTraceback (most recent call last):\n[... 26 lines cut ...]\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={re1['rel_max']*100:.4f}%\")\n ~~~^^^^^^^^^^^\n[line removed by the dashboard scrubber]\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-163.log"},{"i":174,"kind":"raw","long":true,"text":":(bot-2ffcee4b-79d5-44dd-a84a-f855017b64b1B!\n\tsessionID\nThe `EditSet.save()` function's return structure includes module relationships, but the `rel_max` calculation is performed inconsistently between `train_size.py` and `EditSet.save()`. This discrepancy needs correction, specifically within `t15`. Updating the code to use the same logic in both locations.\n\n\n2(bot-2ffcee4b-79d5-44dd-a84a-f855017b64b1:\n{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n _, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re2['modules'].values())*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\",\"Target\":\" print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={re1['rel_max']*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n _, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={re2['rel_max']*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\"}:\n{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \\\"edit_changed\\\": re_ed[\\\"changed\\\"],\\n \\\"edit_net_rel\\\": round(re_ed[\\\"net_rel\\\"], 6),\\n \\\"edit_rel_max\\\": round(max(v[\\\"rel\\\"] for v in re_ed[\\\"modules\\\"].values()), 6),\\n \\\"ctrl_r\\\": re_ct[\\\"r\\\"],\\n \\\"ctrl_changed\\\": re_ct[\\\"changed\\\"],\\n \\\"ctrl_net_rel\\\": round(re_ct[\\\"net_rel\\\"], 6),\\n \\\"ctrl_rel_max\\\": round(max(v[\\\"rel\\\"] for v in re_ct[\\\"modules\\\"].values()), 6),\\n \\\"meta\\\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\\n }))\",\"Target\":\" print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \\\"edit_changed\\\": re_ed[\\\"changed\\\"],\\n \\\"edit_net_rel\\\": round(re_ed[\\\"net_rel\\\"], 6),\\n \\\"edit_rel_max\\\": round(re_ed[\\\"rel_max\\\"], 6),\\n \\\"ctrl_r\\\": re_ct[\\\"r\\\"],\\n \\\"ctrl_changed\\\": re_ct[\\\"changed\\\"],\\n \\\"ctrl_net_rel\\\": round(re_ct[\\\"net_rel\\\"], 6),\\n \\\"ctrl_rel_max\\\": round(re_ct[\\\"rel_max\\\"], 6),\\n \\\"meta\\\": {k: (round(v, 5) if isinstance(v, float) else v\n[... 420 characters cut ...]"},{"i":175,"kind":"raw","long":true,"text":"{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n _, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re2['modules'].values())*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\",\"Target\":\" print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={re1['rel_max']*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n _, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={re2['rel_max']*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\"}:\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py\nprint(\"SELFTEST pure_audit_veto_r3:\", re1[\"r\"], re1[\"changed\"],\n f\"edit={re1['net_rel']*100:.4f}%\", f\"ctrl={rc1['net_rel']*100:.4f}%\",\n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n subprocess.run([PY, str(T / \"check_adapter.py\"), str(td_p / \"e1_ed\")], check=True)\n subprocess.run([PY, str(T / \"check_adapter.py\"), str(td_p / \"e1_ct\")], check=True)\n\n # 2. hybrid_oproj_postveto_r6\n _, _, re2, rc2, m2 = build_pair(\n t9_p, tri_p, \"hybrid_oproj_postveto_r6\",\n mk_stats_path=mk_p, mk_layers_spec=\"5-54\",\n dose_post=15.5, dose_veto=14.5,\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\n out_edit=str(td_p / \"e2_ed\"), out_ctrl=str(td_p / \"e2_ct\")\n )\n print(\"SELFTEST hybrid_oproj_postveto_r6:\", re2[\"r\"], re2[\"changed\"],\n f\"edit={re2['net_rel']*100:.4f}%\", f\"ctrl={rc2['net_rel']*100:.4f}%\",\n f\"max_rel={max(v['rel'] for v in re2['modules'].values())*100:.4f}%\",\n f\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\")\n[... 658 lines cut ...]\n) \"ctrl_changed\": re_ct[\"changed\"],\n7\n3 \"ctrl_net_rel\": round(re_ct[\"net_rel\"], 6),\n7\n3 \"ctrl_rel_max\": round(re_ct[\"rel_max\"], 6),\n_\n[ \"meta\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/175/output.txt"},{"i":176,"kind":"raw","long":true,"text":"{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \\\"edit_changed\\\": re_ed[\\\"changed\\\"],\\n \\\"edit_net_rel\\\": round(re_ed[\\\"net_rel\\\"], 6),\\n \\\"edit_rel_max\\\": round(max(v[\\\"rel\\\"] for v in re_ed[\\\"modules\\\"].values()), 6),\\n \\\"ctrl_r\\\": re_ct[\\\"r\\\"],\\n \\\"ctrl_changed\\\": re_ct[\\\"changed\\\"],\\n \\\"ctrl_net_rel\\\": round(re_ct[\\\"net_rel\\\"], 6),\\n \\\"ctrl_rel_max\\\": round(max(v[\\\"rel\\\"] for v in re_ct[\\\"modules\\\"].values()), 6),\\n \\\"meta\\\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\\n }))\",\"Target\":\" print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \\\"edit_changed\\\": re_ed[\\\"changed\\\"],\\n \\\"edit_net_rel\\\": round(re_ed[\\\"net_rel\\\"], 6),\\n \\\"edit_rel_max\\\": round(re_ed[\\\"rel_max\\\"], 6),\\n \\\"ctrl_r\\\": re_ct[\\\"r\\\"],\\n \\\"ctrl_changed\\\": re_ct[\\\"changed\\\"],\\n \\\"ctrl_net_rel\\\": round(re_ct[\\\"net_rel\\\"], 6),\\n \\\"ctrl_rel_max\\\": round(re_ct[\\\"rel_max\\\"], 6),\\n \\\"meta\\\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\\n }))\"}2\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py\nprint(json.dumps({\n \"recipe\": args.recipe,\n \"edit_r\": re_ed[\"r\"],\n \"edit_changed\": re_ed[\"changed\"],\n \"edit_net_rel\": round(re_ed[\"net_rel\"], 6),\n \"edit_rel_max\": round(max(v[\"rel\"] for v in re_ed[\"modules\"].values()), 6),\n \"ctrl_r\": re_ct[\"r\"],\n \"ctrl_changed\": re_ct[\"changed\"],\n \"ctrl_net_rel\": round(re_ct[\"net_rel\"], 6),\n \"ctrl_rel_max\": round(max(v[\"rel\"] for v in re_ct[\"modules\"].values()), 6),\n \"meta\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\n }))\nprint(json.dumps({\n \"recipe\": args.recipe,\n \"edit_r\": re_ed[\"r\"],\n \"edit_changed\": re_ed[\"changed\"],\n \"edit_net_rel\": round(re_ed[\"net_rel\"], 6),\n \"edit_rel_max\": round(re_ed[\"rel_max\"], 6),\n[... 646 lines cut ...]\n3 \"ctrl_net_rel\": round(re_ct[\"net_rel\"], 6),\n7\n3 \"ctrl_rel_max\": round(re_ct[\"rel_max\"], 6),\nW\nS \"ctrl_rel_max\": round(max(v[\"rel\"] for v in re_ct[\"modules\"].values()), 6),\n_\n[ \"meta\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/176/output.txt"},{"i":177,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Re-run t15_build.py selftest\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-177.log\"\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest':\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\nCommand exited with code 1.\n\nCommand output:\nTraceback (most recent call last):\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 658, in \n main()\n ~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 618, in main\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in \n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n[... 13 lines cut ...]\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in \n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~^^^^^^^\n[line removed by the dashboard scrubber]\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/177/output.txt"},{"i":178,"kind":"raw","long":false,"text":":(bot-39382792-c2b4-4f7a-bd3a-ca02efa50821B!\n\tsessionID\nInitial focus is on creating a pre-test script to validate CPU execution. The objective is to ensure the script's output mirrors a specific function's behavior accurately. The target execution time for the pre-test script is between 6-8 minutes.\n\n\nA quick bit-for-bit verification is required to confirm batched loop execution matches the target function, ensuring exact bit identity. This involves testing with unseen probes to validate the CPU pass. The probe set consists of unseen episodes, carefully selected to provide broad coverage.\n\n[line removed by the dashboard scrubber]\n\n[line removed by the dashboard scrubber]\n\n\n[line removed by the dashboard scrubber]\n\n\nChunking the `F.linear` operation into smaller slices appears feasible, reducing peak transient RAM usage to under 7 GB. Attention speed analysis reveals rapid processing for sliding-window layers, approximately 15 ms per call, totaling about 1.0s/layer. Evaluating global attention layers indicates that the workload can be handled efficiently, considering the performance benchmark.\n\n\n2(bot-39382792-c2b4-4f7a-bd3a-ca02efa50821:3\nL{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177\"}:3"},{"i":179,"kind":"raw","long":true,"text":"L{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177\"}:3\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177\nCreated At: 2026-11-14T15:27:18-05:00\nCompleted At: 2026-11-14T15:27:18-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177\nStatus: DONE\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-177.log\nLog output:\nTraceback (most recent call last):\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 658, in \n main()\n ~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 618, in main\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in \n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n[... 17 lines cut ...]\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in \n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~^^^^^^^\n[line removed by the dashboard scrubber]\n```2o\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/179/output.txt"},{"i":180,"kind":"raw","long":true,"text":"[Message] timestamp=2026-11-14T20:27:01Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-177\" finished with result:\nCommand exited with code 1.\n\nCommand output:\nTraceback (most recent call last):\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 658, in \n main()\n ~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 618, in main\n selftest_real()\n ~~~~~~~~~~~~~^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in selftest_real\n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in \n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~^^^^^^^\n[line removed by the dashboard scrubber]\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-177.log\n[... 32 lines cut ...]\n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py\", line 572, in \n f\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\")\n ~^^^^^^^\n[line removed by the dashboard scrubber]\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-177.log"},{"i":181,"kind":"raw","long":true,"text":":(bot-48fce05e-4658-4c4d-8f4a-67acffc628b1B!\n\tsessionID\n[line removed by the dashboard scrubber]\n\n\n2(bot-48fce05e-4658-4c4d-8f4a-67acffc628b1:\n{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" e1_ed, _, re1, rc1, m1 = build_pair(\\n t9_p, tri_p, \\\"pure_audit_veto_r3\\\",\\n dose_all=6.0, dose_post=16.5, dose_veto=15.0,\\n out_edit=str(td_p / \\\"e1_ed\\\"), out_ctrl=str(td_p / \\\"e1_ct\\\")\\n )\\n print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in e1_ed.sizes().values())*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n e2_ed, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in e2_ed.sizes().values())*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\",\"Target\":\" _, _, re1, rc1, m1 = build_pair(\\n t9_p, tri_p, \\\"pure_audit_veto_r3\\\",\\n dose_all=6.0, dose_post=16.5, dose_veto=15.0,\\n out_edit=str(td_p / \\\"e1_ed\\\"), out_ctrl=str(td_p / \\\"e1_ct\\\")\\n )\\n print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n _, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re2['modules'].values())*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\"}:\n{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" e_ed, e_ct, re_ed, re_ct, meta = build_pair(\\n t9_stats_path=args.t9_stats,\\n tri_stats_path=args.tri_stats,\\n recipe=args.recipe,\\n mlp_layers_spec=args.mlp_layers,\\n mk_stats_path=args.mk_stats,\\n mk_layers_spec=args.mk_layers,\\n dose_all=args.dose_all,\\n dose_post=args.dose_post,\\n dose_veto=args.dose_veto,\\n gamma=args.gamma,\\n eta_max=args.eta_max,\\n max_col_rel=args.max_col_rel,\\n r_mk=args.r_mk,\\n alpha_debias=args.alpha_debias,\\n target_oproj_net_rel=args.target_oproj_net_rel,\\n max_mat_rel=args.max_mat_rel,\\n z_target=args.z_target,\\n seed=args.seed,\\n out_edit=args.out_edit,\\n out_ctrl=args.out_ctrl,\\n )\\n print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \n[... 2299 characters cut ...]"},{"i":182,"kind":"raw","long":true,"text":"{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" e1_ed, _, re1, rc1, m1 = build_pair(\\n t9_p, tri_p, \\\"pure_audit_veto_r3\\\",\\n dose_all=6.0, dose_post=16.5, dose_veto=15.0,\\n out_edit=str(td_p / \\\"e1_ed\\\"), out_ctrl=str(td_p / \\\"e1_ct\\\")\\n )\\n print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in e1_ed.sizes().values())*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n e2_ed, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in e2_ed.sizes().values())*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\",\"Target\":\" _, _, re1, rc1, m1 = build_pair(\\n t9_p, tri_p, \\\"pure_audit_veto_r3\\\",\\n dose_all=6.0, dose_post=16.5, dose_veto=15.0,\\n out_edit=str(td_p / \\\"e1_ed\\\"), out_ctrl=str(td_p / \\\"e1_ct\\\")\\n )\\n print(\\\"SELFTEST pure_audit_veto_r3:\\\", re1[\\\"r\\\"], re1[\\\"changed\\\"],\\n f\\\"edit={re1['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc1['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re1['modules'].values())*100:.4f}%\\\")\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ed\\\")], check=True)\\n subprocess.run([PY, str(T / \\\"check_adapter.py\\\"), str(td_p / \\\"e1_ct\\\")], check=True)\\n\\n # 2. hybrid_oproj_postveto_r6\\n _, _, re2, rc2, m2 = build_pair(\\n t9_p, tri_p, \\\"hybrid_oproj_postveto_r6\\\",\\n mk_stats_path=mk_p, mk_layers_spec=\\\"5-54\\\",\\n dose_post=15.5, dose_veto=14.5,\\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\\n out_edit=str(td_p / \\\"e2_ed\\\"), out_ctrl=str(td_p / \\\"e2_ct\\\")\\n )\\n print(\\\"SELFTEST hybrid_oproj_postveto_r6:\\\", re2[\\\"r\\\"], re2[\\\"changed\\\"],\\n f\\\"edit={re2['net_rel']*100:.4f}%\\\", f\\\"ctrl={rc2['net_rel']*100:.4f}%\\\",\\n f\\\"max_rel={max(v['rel'] for v in re2['modules'].values())*100:.4f}%\\\",\\n f\\\"oproj_rel={m2['oproj_net_rel']*100:.4f}%\\\")\"}:\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py\ne1_ed, _, re1, rc1, m1 = build_pair(\n t9_p, tri_p, \"pure_audit_veto_r3\",\n dose_all=6.0, dose_post=16.5, dose_veto=15.0,\n out_edit=str(td_p / \"e1_ed\"), out_ctrl=str(td_p / \"e1_ct\")\n )\n print(\"SELFTEST pure_audit_veto_r3:\", re1[\"r\"], re1[\"changed\"],\n f\"edit={re1['net_rel']*100:.4f}%\", f\"ctrl={rc1['net_rel']*100:.4f}%\",\n f\"max_rel={max(v['rel'] for v in e1_ed.sizes().values())*100:.4f}%\")\n subprocess.run([PY, str(T / \"check_adapter.py\"), str(td_p / \"e1_ed\")], check=True)\n subprocess.run([PY, str(T / \"check_adapter.py\"), str(td_p / \"e1_ct\")], check=True)\n\n # 2. hybrid_oproj_postveto_r6\n e2_ed, _, re2, rc2, m2 = build_pair(\n t9_p, tri_p, \"hybrid_oproj_postveto_r6\",\n mk_stats_path=mk_p, mk_layers_spec=\"5-54\",\n dose_post=15.5, dose_veto=14.5,\n r_mk=6, alpha_debias=1.0, target_oproj_net_rel=0.0032,\n out_edit=str(td_p / \"e2_ed\"), out_ctrl=str(td_p / \"e2_ct\")\n[... 672 lines cut .\n[... 412 characters cut ...]"},{"i":183,"kind":"raw","long":true,"text":"{\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py\",\"Replacement\":\" e_ed, e_ct, re_ed, re_ct, meta = build_pair(\\n t9_stats_path=args.t9_stats,\\n tri_stats_path=args.tri_stats,\\n recipe=args.recipe,\\n mlp_layers_spec=args.mlp_layers,\\n mk_stats_path=args.mk_stats,\\n mk_layers_spec=args.mk_layers,\\n dose_all=args.dose_all,\\n dose_post=args.dose_post,\\n dose_veto=args.dose_veto,\\n gamma=args.gamma,\\n eta_max=args.eta_max,\\n max_col_rel=args.max_col_rel,\\n r_mk=args.r_mk,\\n alpha_debias=args.alpha_debias,\\n target_oproj_net_rel=args.target_oproj_net_rel,\\n max_mat_rel=args.max_mat_rel,\\n z_target=args.z_target,\\n seed=args.seed,\\n out_edit=args.out_edit,\\n out_ctrl=args.out_ctrl,\\n )\\n print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \\\"edit_changed\\\": re_ed[\\\"changed\\\"],\\n \\\"edit_net_rel\\\": round(re_ed[\\\"net_rel\\\"], 6),\\n \\\"edit_rel_max\\\": round(max(v[\\\"rel\\\"] for v in e_ed.sizes().values()), 6),\\n \\\"ctrl_r\\\": re_ct[\\\"r\\\"],\\n \\\"ctrl_changed\\\": re_ct[\\\"changed\\\"],\\n \\\"ctrl_net_rel\\\": round(re_ct[\\\"net_rel\\\"], 6),\\n \\\"ctrl_rel_max\\\": round(max(v[\\\"rel\\\"] for v in e_ct.sizes().values()), 6),\\n \\\"meta\\\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\\n }))\",\"Target\":\" _, _, re_ed, re_ct, meta = build_pair(\\n t9_stats_path=args.t9_stats,\\n tri_stats_path=args.tri_stats,\\n recipe=args.recipe,\\n mlp_layers_spec=args.mlp_layers,\\n mk_stats_path=args.mk_stats,\\n mk_layers_spec=args.mk_layers,\\n dose_all=args.dose_all,\\n dose_post=args.dose_post,\\n dose_veto=args.dose_veto,\\n gamma=args.gamma,\\n eta_max=args.eta_max,\\n max_col_rel=args.max_col_rel,\\n r_mk=args.r_mk,\\n alpha_debias=args.alpha_debias,\\n target_oproj_net_rel=args.target_oproj_net_rel,\\n max_mat_rel=args.max_mat_rel,\\n z_target=args.z_target,\\n seed=args.seed,\\n out_edit=args.out_edit,\\n out_ctrl=args.out_ctrl,\\n )\\n print(json.dumps({\\n \\\"recipe\\\": args.recipe,\\n \\\"edit_r\\\": re_ed[\\\"r\\\"],\\n \\\"edit_changed\\\": re_ed[\\\"changed\\\"],\\n \\\"edit_net_rel\\\": round(re_ed[\\\"net_rel\\\"], 6),\\n \\\"edit_rel_max\\\": round(max(v[\\\"rel\\\"] for v in re_ed[\\\"modules\\\"].values()), 6),\\n \\\"ctrl_r\\\": re_ct[\\\"r\\\"],\\n \\\"ctrl_changed\\\": re_ct[\\\"changed\\\"],\\n \\\"ctrl_net_rel\\\": round(re_ct[\\\"net_rel\\\"], 6),\\n \\\"ctrl_rel_max\\\": round(max(v[\\\"rel\\\"] for v in re_ct[\\\"modules\\\"].values()), 6),\\n \\\"meta\\\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\\n }))\"}2\n2C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py\ne_ed, e_ct, re_ed, re_ct, meta = build_pair(\n t9_stats_path=args.t9_stats,\n tri_stats_path=args.tri_stats,\n recipe=args.recipe,\n mlp_layers_spec=args.mlp_layers,\n mk_stats_path=args.mk_stats,\n mk_layers_spec=args.mk_layers,\n dose_all=args.dose_all,\n dose_post=args.dose_post,\n dose_veto=args.dose_veto,\n gamma=args.gamma,\n eta_max=args.eta_max,\n max_col_rel=args.max_col_rel,\n r_mk=args.r_mk,\n alpha_debias=args.alpha_debias,\n target_oproj_net_rel=args.target_oproj_net_rel,\n max_mat_rel=args.max_mat_rel,\n z_target=args.z_target,\n[... 692 lines cut ...]\n3 \"ctrl_net_rel\": round(re_ct[\"net_rel\"], 6),\nW\nS \"ctrl_rel_max\": round(max(v[\"rel\"] for v in re_ct[\"modules\"].values()), 6),\nS\nO \"ctrl_rel_max\": round(max(v[\"rel\"] for v in e_ct.sizes().values()), 6),\n_\n[ \"meta\": {k: (round(v, 5) if isinstance(v, float) else v) for k, v in meta.items()},\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.syste\n[... 32 characters cut ...]"},{"i":184,"kind":"raw","long":false,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Verify t15_build.py selftest passes\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-184.log\"\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest':#Verify t15_build.py selftest passesB\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\nCommand exited with code 0.\n\nCommand output:\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\nterminalJ%\n#verify t15_build.py selftest passesR\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/184/output.txt"},{"i":185,"kind":"raw","long":false,"text":":(bot-f18de41b-5657-497c-ab2e-6b6f54df4ee9B!\n\tsessionID\nInitial setup involves preparing a pre-test script to validate data hygiene. The script will load and verify the integrity of specific data files. Data sources and their verification steps are being defined.\n\n\n[line removed by the dashboard scrubber]\n\nImplemented a bit-for-bit verification of the initial sequence using a simplified model configuration (layers 0 and 1) to confirm that the foundational processing steps are functioning as intended. Confirmed identical outputs.\n\n\n[line removed by the dashboard scrubber]\n\n\n[line removed by the dashboard scrubber]\n\nIdentified that layer 0 across all 9 arms shares an identical state before the output projection. This suggests an optimization path to reduce redundant calculations for these identical initial states.\n\n\nObserved that attention input distinction starts at layer 1, streamlining the initial calculations. Batching all nine arms into one GEMM reduces linear layer time to under 1.8 seconds per layer. Total wall-clock time is estimated between 3.5 to 4.5 minutes for all nine arms across sixty layers.\n\nExtracted metrics at layer 59, specifically at decision points, for both `closeprobe.table` and `delimprobe.table` across unseen calls, focusing on log probabilities and error rates.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-f18de41b-5657-497c-ab2e-6b6f54df4ee9:8\nL{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184\"}:7\nu^|DP^3OGxH\u00f9w\u07f3@X\u069bFHq1\u03c6(2$\\W\u02b06.W&\u3b9b\t= -0.05` guard at `close` and `cont`).\n3. `delimprobe` metrics (`delim_error == 0.000` at `<|\"|>` string delimiters `tok 52` and `arg` positions on calls 2+).\n[line removed by the dashboard scrubber]\n tool-syntax `KL` & top-1 flip rate, and pre-submit `d_logp(submit_patch - run_command)` shift.\n\"\"\"\nimport gc\nimport json\nimport os\nimport pathlib\nimport shutil\nimport sys\nimport time\n\n[... 1051 lines cut ...]\n. rep_path = SCR / \"t15_pretest_report.json\"\n=\n9 rep_path.write_text(json.dumps(out_report, indent=2))\n3\n/ shutil.rmtree(CAND_DIR, ignore_errors=True)\n_\n[ print(f\"\\n[{time.time()-t0:.1f}s] Saved {rep_path} and cleaned {CAND_DIR}\", flush=True)\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/190/output.txt"},{"i":191,"kind":"raw","long":false,"text":"L{\"Action\":\"status\",\"TaskId\":\"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184\"}2\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184\nCreated At: 2026-11-14T15:30:16-05:00\nCompleted At: 2026-11-14T15:30:19-05:00\nTask: 4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184\nStatus: DONE\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-184.log\nLog output:\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\n\nLast progress: 48s ago\ntasksJ%\n#Verify t15_build.py selftest passesR\n**Status**: DONE \u2022 **Last progress**: 48s ago\n\n```\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\n```2o\n4type.googleapis.com/exa.cortex.core.tools.ManageTask\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/191/output.txt"},{"i":192,"kind":"raw","long":true,"text":"[Message] timestamp=2026-11-14T20:29:30Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-184\" finished with result:\nCommand exited with code 0.\n\nCommand output:\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-184.log\n,Verify t15_build.py selftest passes finishedR\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_build.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=8 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_build.py --selftest'\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\n[... 8 lines cut ...]\nOK e1_ed: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06986 at 11.down_proj\nOK e1_ct: 180 modules changed (of 180 present), r=3, max |dW|_F/|W|_F 0.06984 at 11.down_proj\nOK e2_ed: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nOK e2_ct: 230 modules changed (of 230 present), r=6, max |dW|_F/|W|_F 0.06406 at 11.down_proj\nSELFTEST pure_audit_veto_r3: 3 180 edit=1.2987% ctrl=1.2987% max_rel=6.9835%\nSELFTEST hybrid_oproj_postveto_r6: 6 230 edit=1.1468% ctrl=1.1468% max_rel=6.4064% oproj_rel=0.3200%\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-184.log"},{"i":193,"kind":"raw","long":false,"text":":(bot-ef5d8316-d4d9-46cb-a8dc-10bc85500b6dB!\n\tsessionID\nThe self-test output shows 180 modules changed in both `e1_ed` and `e1_ct`, suggesting a widespread modification. The relatively low maximum weight change indicates that the changes are likely small-scale adjustments. This finding points to potential configuration updates or minor code revisions impacting a significant portion of the system.\n\n\nThe new self-test output reveals changes across many modules in both `e2_ed` and `e2_ct`, similar to previous results, but with a different test name. The relative weight change, while still small, is consistently near the previous maximum. The next step involves running a CPU pre-test to gather more precise data.\n\n\n2(bot-ef5d8316-d4d9-46cb-a8dc-10bc85500b6d:\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_cpu_pretest.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=16 MKL_NUM_THREADS=16 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py'\",\"WaitMsBeforeAsync\":5000,\"toolSummary\":\"Run exact CPU g31 pre-test battery\"}:"},{"i":194,"kind":"raw","long":true,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\t15_cpu_pretest.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=16 MKL_NUM_THREADS=16 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py'\",\"WaitMsBeforeAsync\":5000,\"toolSummary\":\"Run exact CPU g31 pre-test battery\"}:\n-4fbddbc5-e478-44c0-a42f-2366c93d8394/task-194\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-194.log\n[line removed by the dashboard scrubber]\n [pre_edit ] [task] call= 1 n=2910 cp=3 dp=11 sub=0\n [pre_edit ] jsvine__pdfplumber.02ff4313.func_pm_remove_assign__1v9soh1j call= 2 n=3339 cp=2 dp=11 sub=0\n [post_edit] [task] call=21 n=3005 cp=2 dp=11 sub=0\n [post_edit] [task] call=41 n=3359 cp=4 dp=7 sub=0\n [pre_sub ] [task] call=14 n=5109 cp=2 dp=7 sub=1\n [pre_sub ] django-money__django-money.835c1ab8.combine_module__bqggrnha call=18 n=5504 cp=2 dp=7 sub=1\n\"\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_cpu_pretest.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=16 MKL_NUM_THREADS=16 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py':\"Run exact CPU g31 pre-test batteryB\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_cpu_pretest.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=16 MKL_NUM_THREADS=16 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py'\nCommand exited with code 1.\n\nCommand output:\n[line removed by the dashboard scrubber]\n [pre_edit ] [task] call= 1 n=2910 cp=3 dp=11 sub=0\n [pre_edit ] jsvine__pdfplumber.02ff4313.func_pm_remove_assign__1v9soh1j call= 2 n=3339 cp=2 dp=11 sub=0\n [post_edit] [task] call=21 n=3005 cp=2 dp=11 sub=0\n[... 32 lines cut ...]\n Layer 11/59 done in 115.62s (elapsed 1158.0s)\n Layer 19/59 done in 79.57s (elapsed 1832.3s)\n Layer 29/59 done in 116.72s (elapsed 2703.4s)\n Layer 39/59 done in 82.30s (elapsed 3541.2s)\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\t15_cpu_pretest.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py; ssh -o BatchMode=yes wrx90 'OMP_NUM_THREADS=16 MKL_NUM_THREADS=16 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/t15_cpu_pretest.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/194/output.txt"},{"i":195,"kind":"raw","long":false,"text":":(bot-c6a37e62-5d8f-497a-9965-4d58da506cd0B!\n\tsessionID\nTask 194 shows successful execution with expected pre- and post-edit calls. The calls involve distinct, previously unseen functionalities, suggesting effective integration of diverse components. Further validation is needed, but the preliminary results are positive.\n\n\n2(bot-c6a37e62-5d8f-497a-9965-4d58da506cd0:\nj{\"EndLine\":180,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\finalize_t12_entries.py\",\"StartLine\":1}:"},{"i":196,"kind":"raw","long":true,"text":"j{\"EndLine\":180,\"Path\":\"C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\finalize_t12_entries.py\",\"StartLine\":1}:\n=C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\finalize_t12_entries.py\nCreated At: 2026-11-14T15:30:52-05:00\nCompleted At: 2026-11-14T15:30:52-05:00\nShowing lines 1-180 of 285\n1: #!/usr/bin/env python3\n2: \"\"\"Turn 12 complete CPU finalizer (author: gemini):\n3: 1. Packages Entry 1 (`tri-phase-concise-audit-veto`, r=3, 180 MLP matrices) completely through `READY` FIRST.\n[line removed by the dashboard scrubber]\n5: 3. Cleans temporary candidate directories in `scratch/` and writes updated `NOTES.md` (< 600 words).\n6: \"\"\"\n7: import json\n8: import pathlib\n9: import re\n10: import shutil\n11: import sys\n12: \n13: import torch\n14: \n15: R = pathlib.Path(\"/home/keith/gemma-v2\")\n[... 161 lines cut ...]\n177: \n178: package_t12.finalize_entry_with_ready(slug1, rec1)\n179: \n180: # =========================================================================\nL\nEfile:///C:/Users/Owner/wsp31_loop/work/gemini/finalize_t12_entries.py\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\n=C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\finalize_t12_entries.py"},{"i":197,"kind":"raw","long":true,"text":":(bot-a9ddbb81-33fe-400a-b925-32dd4f480bb1B!\n\tsessionID\nAnalyzing `finalize_t12_entries.py` alongside the forensic data reveals a critical area of interest. Lines 171-175 appear central to the pre-run prediction and falsification process. The script's logic here warrants further scrutiny, especially in relation to the Turn-15 autopsy results.\n\n\nInitial observations suggest `P_focus`'s impact on `read_file` and `audit_post` reliability in Turn 12 necessitates careful replication in Turn 15. The falsification condition, triggered by performance drops, highlights the need to validate the causal effect of `P_focus` on these metrics, especially in light of Turn 12's varying outcomes. The Turn 15 test focuses on isolating the effects of `P_focus` removal across different MLP neurons and input data.\n\n\nExamining the proposed entries, specifically Entry 2, reveals a significant modification: the removal of `P_focus` within `t12_mk_stats`. This involves weight adjustments using Empirical-Bayes, calibration to a network norm, and composition on numerous disjoint matrices controlled by a two-neuron MLP. A local script, `code/package_t15.py`, is being prepared to ensure the requirements are fully met, including the length check.\n\n\n[line removed by the dashboard scrubber]\n\n\n2(bot-a9ddbb81-33fe-400a-b925-32dd4f480bb1:e\nA{\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Turn 15 deterministic packager, bit-for-bit SHA256 rebuild verifier, check_adapter + train_size runner,\\nand exact runner.py ingest validator for author gemini.\\n\\\"\\\"\\\"\\nimport hashlib\\nimport json\\nimport re\\nimport shutil\\nimport stat\\nimport subprocess\\nimport sys\\nfrom pathlib import Path\\n\\nR = Path(\\\"/home/keith/gemma-v2\\\")\\nsys.path.insert(0, str(R / \\\"wsp31\\\" / \\\"queue\\\"))\\nimport runner\\n\\nPY = str(R / \\\"tii-venv\\\" / \\\"bin\\\" / \\\"python\\\")\\nT = R / \\\"wsp31\\\" / \\\"tools\\\"\\nG = R / \\\"wsp31\\\" / \\\"authors\\\" / \\\"gemini\\\"\\nCODE = G / \\\"code\\\"\\nQ_DIR = G / \\\"queue\\\"\\nSCR = G / \\\"scratch\\\"\\n\\n\\ndef sha256_file(p: Path) -\\u003e str:\\n h = hashlib.sha256()\\n with p.open(\\\"rb\\\") as f:\\n for chunk in iter(lambda: f.read(1 \\u003c\\u003c 20), b\\\"\\\"):\\n h.update(chunk)\\n return h.hexdigest()\\n\\n\\ndef write_lf(path: Path, content: str, executable: bool = False):\\n path.parent.mkdir(parents=True, exist_ok=True)\\n with path.open(\\\"w\\\", encoding=\\\"utf-8\\\", newline=\\\"\\\\n\\\") as f:\\n f.write(content)\\n if executable:\\n path.chmod(path.stat().st_mode | stat.S_IXUSR | stat.S_IXGRP | stat.S_IXOTH)\\n\\n\\ndef make_build_sh_t15(cfg: dict) -\\u003e str:\\n recipe = cfg[\\\"recipe\\\"]\\n if recipe == \\\"pure_audit_veto_r3\\\":\\n return f\\\"\\\"\\\"#!/usr/bin/env bash\\nset -euo pipefail\\nexport OMP_NUM_THREADS=8\\nexport MKL_NUM_THREADS=8\\nR=\\\"/home/keith/gemma-v2\\\"\\nPY=\\\"$R/tii-venv/bin/python\\\"\\nCODE=\\\"$R/wsp31/authors/gemini/code\\\"\\nOUT_DIR=\\\"${{1:-$(cd \\\"$(dirname \\\"$0\\\")\\\" \\u0026\\u0026 pwd)}}\\\"\\n\\nmkdir -p \\\"$OUT_DIR\\\"\\n\\\"$PY\\\" \\\"$CODE/t15_build.py\\\" \\\\\\\\\\n --t9-stats \\\"$CODE/data/t9_stats.pt\\\" \\\\\\\\\\n --tri-stats \\\"$CODE/data/t12_tri_stats.pt\\\" \\\\\\\\\\n --recipe \\\"pure_audit_veto_r3\\\" \\\\\\\\\\n --mlp-layers \\\"{cfg.get('mlp_layers', '0-59')}\\\" \\\\\\\\\\n --dose-all {cfg['dose_all']} \\\\\\\\\\n --dose-post {cfg['dose_post']} \\\\\\\\\\n --dose-veto {cfg['dose_veto']} \\\\\\\\\\n --gamma {cfg.get('gamma', 0.90)} \\\\\\\\\\n --eta-max {cfg['eta_max']} \\\\\\\\\\n --max-col-rel {cfg['max_col_rel']} \\\\\\\\\\n --z-target {cfg.get('z_target', 3.0)} \\\\\\\\\\n --seed {cfg['seed']} \\\\\\\\\\n --out-edit \\\"$OUT_DIR/edit\\\" \\\\\\\\\\n --out-ctrl \\\"$OUT_DIR/ctrl\\\"\\n\\\"\\\"\\\"\\n elif recipe == \\\"hybrid_oproj_postveto_r6\\\":\\n return f\\\"\\\"\\\"#!/usr/bin/env bash\\nset -euo pipefail\\nexport OMP_NUM_THREADS=8\\nexport MKL_NUM_THREADS=8\\nR=\\\"/home/keith/gemma-v2\\\"\\nPY=\\\"$R/tii-venv/bin/python\\\"\\nCODE=\\\"$R/wsp31/authors/gemini/code\\\"\\nOUT_DIR=\\\"${{1:-$(cd \\\"$(dirname \\\"$0\\\")\\\" \\u0026\\u0026 pwd)}}\\\"\\n\\nmkdir -p \\\"$OUT_DIR\\\"\\n\\\"$PY\\\" \\\"$CODE/t15_build.py\\\" \\\\\\\\\\n --t9-stats \\\"$CODE/data/t9_stats.pt\\\" \\\\\\\\\\n --\n[... 5677 characters cut ...]"},{"i":198,"kind":"raw","long":true,"text":"A{\"Content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Turn 15 deterministic packager, bit-for-bit SHA256 rebuild verifier, check_adapter + train_size runner,\\nand exact runner.py ingest validator for author gemini.\\n\\\"\\\"\\\"\\nimport hashlib\\nimport json\\nimport re\\nimport shutil\\nimport stat\\nimport subprocess\\nimport sys\\nfrom pathlib import Path\\n\\nR = Path(\\\"/home/keith/gemma-v2\\\")\\nsys.path.insert(0, str(R / \\\"wsp31\\\" / \\\"queue\\\"))\\nimport runner\\n\\nPY = str(R / \\\"tii-venv\\\" / \\\"bin\\\" / \\\"python\\\")\\nT = R / \\\"wsp31\\\" / \\\"tools\\\"\\nG = R / \\\"wsp31\\\" / \\\"authors\\\" / \\\"gemini\\\"\\nCODE = G / \\\"code\\\"\\nQ_DIR = G / \\\"queue\\\"\\nSCR = G / \\\"scratch\\\"\\n\\n\\ndef sha256_file(p: Path) -\\u003e str:\\n h = hashlib.sha256()\\n with p.open(\\\"rb\\\") as f:\\n for chunk in iter(lambda: f.read(1 \\u003c\\u003c 20), b\\\"\\\"):\\n h.update(chunk)\\n return h.hexdigest()\\n\\n\\ndef write_lf(path: Path, content: str, executable: bool = False):\\n path.parent.mkdir(parents=True, exist_ok=True)\\n with path.open(\\\"w\\\", encoding=\\\"utf-8\\\", newline=\\\"\\\\n\\\") as f:\\n f.write(content)\\n if executable:\\n path.chmod(path.stat().st_mode | stat.S_IXUSR | stat.S_IXGRP | stat.S_IXOTH)\\n\\n\\ndef make_build_sh_t15(cfg: dict) -\\u003e str:\\n recipe = cfg[\\\"recipe\\\"]\\n if recipe == \\\"pure_audit_veto_r3\\\":\\n return f\\\"\\\"\\\"#!/usr/bin/env bash\\nset -euo pipefail\\nexport OMP_NUM_THREADS=8\\nexport MKL_NUM_THREADS=8\\nR=\\\"/home/keith/gemma-v2\\\"\\nPY=\\\"$R/tii-venv/bin/python\\\"\\nCODE=\\\"$R/wsp31/authors/gemini/code\\\"\\nOUT_DIR=\\\"${{1:-$(cd \\\"$(dirname \\\"$0\\\")\\\" \\u0026\\u0026 pwd)}}\\\"\\n\\nmkdir -p \\\"$OUT_DIR\\\"\\n\\\"$PY\\\" \\\"$CODE/t15_build.py\\\" \\\\\\\\\\n --t9-stats \\\"$CODE/data/t9_stats.pt\\\" \\\\\\\\\\n --tri-stats \\\"$CODE/data/t12_tri_stats.pt\\\" \\\\\\\\\\n --recipe \\\"pure_audit_veto_r3\\\" \\\\\\\\\\n --mlp-layers \\\"{cfg.get('mlp_layers', '0-59')}\\\" \\\\\\\\\\n --dose-all {cfg['dose_all']} \\\\\\\\\\n --dose-post {cfg['dose_post']} \\\\\\\\\\n --dose-veto {cfg['dose_veto']} \\\\\\\\\\n --gamma {cfg.get('gamma', 0.90)} \\\\\\\\\\n --eta-max {cfg['eta_max']} \\\\\\\\\\n --max-col-rel {cfg['max_col_rel']} \\\\\\\\\\n --z-target {cfg.get('z_target', 3.0)} \\\\\\\\\\n --seed {cfg['seed']} \\\\\\\\\\n --out-edit \\\"$OUT_DIR/edit\\\" \\\\\\\\\\n --out-ctrl \\\"$OUT_DIR/ctrl\\\"\\n\\\"\\\"\\\"\\n elif recipe == \\\"hybrid_oproj_postveto_r6\\\":\\n return f\\\"\\\"\\\"#!/usr/bin/env bash\\nset -euo pipefail\\nexport OMP_NUM_THREADS=8\\nexport MKL_NUM_THREADS=8\\nR=\\\"/home/keith/gemma-v2\\\"\\nPY=\\\"$R/tii-venv/bin/python\\\"\\nCODE=\\\"$R/wsp31/authors/gemini/code\\\"\\nOUT_DIR=\\\"${{1:-$(cd \\\"$(dirname \\\"$0\\\")\\\" \\u0026\\u0026 pwd)}}\\\"\\n\\nmkdir -p \\\"$OUT_DIR\\\"\\n\\\"$PY\\\" \\\"$CODE/t15_build.py\\\" \\\\\\\\\\n --t9-stats \\\"$CODE/data/t9_stats.pt\\\" \\\\\\\\\\n --tri-stats \\\"$CODE/data/t12_tri_stats.pt\\\" \\\\\\\\\\n --mk-stats \\\"$CODE/data/t12_mk_stats.pt\\\" \\\\\\\\\\n --recipe \\\"hybrid_oproj_postveto_r6\\\" \\\\\\\\\\n --mlp-layers \\\"{cfg.get('mlp_layers', '0-59')}\\\" \\\\\\\\\\n --mk-layers \\\"{cfg.get('mk_layers', '5-54')}\\\" \\\\\\\\\\n --r-mk {cfg.get('r_mk', 6)} \\\\\\\\\\n --alpha-debias {cfg.get('alpha_debias', 1.0)} \\\\\\\\\\n --target-oproj-net-rel {cfg['target_oproj_net_rel']} \\\\\\\\\\n --max-mat-rel {cfg['max_mat_rel']} \\\\\\\\\\n --dose-post {cfg['dose_post']} \\\\\\\\\\n --dose-veto {cfg['dose_veto']} \\\\\\\\\\n --gamma {cfg.get('gamma', 0.90)} \\\\\\\\\\n --eta-max {cfg['eta_max']} \\\\\\\\\\n --max-col-rel {cfg['max_col_rel']} \\\\\\\\\\n --z-target {cfg.get('z_target', 3.0)} \\\\\\\\\\n --seed {cfg['seed']} \\\\\\\\\\n --out-edit \\\"$OUT_DIR/edit\\\" \\\\\\\\\\n --out-ctrl \\\"$OUT_DIR/ctrl\\\"\\n\\\"\\\"\\\"\\n else:\\n raise ValueError(f\\\"Unknown recipe: {recipe}\\\")\\n\\n\\ndef build_and_verify_adapters(slug: str, cfg: dict):\\n assert re.fullmatch(r\\\"[a-z0-9][a-z0-9-]{2,39}\\\", slug), f\\\"Invalid slug: {slug}\\\"\\n entry = Q_DIR / slug\\n if entry.exists():\\n assert not (entry / \\\"READY\\\").exists(), f\\\"{entry}/READY already exists!\\\"\\n shutil.rmtree(entry)\\n entry.mkdir(parents=True, exist_ok=True)\\n\\n bsh = entry / \\\"build.sh\\\"\\n write_lf(bsh, make_build_sh_t15(cfg), executable=True)\\n\\n # \n[... 5254 characters cut ...]"},{"i":199,"kind":"raw","long":false,"text":":(bot-3e0a38fa-7d11-4f4d-8106-0dab65164ccbB!\n\tsessionID\nCopying the forensic script to the target environment. Also updating the interim notes to record the ongoing Turn-15 autopsy data and script transfer. This will ensure traceability of actions.\n\n\n2(bot-3e0a38fa-7d11-4f4d-8106-0dab65164ccb:*\n[line removed by the dashboard scrubber]\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\package_t15.py C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\write_notes_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/write_notes_t15.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Upload package_t15 and update interim NOTES.md\"}Z"},{"i":200,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n8C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\write_notes_t15.py\n!\n!#!/usr/bin/env python3\n\"\"\"Write Turn-15 NOTES.md on wrx90 and enforce strictly < 600 words.\"\"\"\nimport pathlib\nimport sys\n\nNOTES_PATH = pathlib.Path(\"/home/keith/gemma-v2/wsp31/authors/gemini/NOTES.md\")\n\nINTERIM_NOTES = \"\"\"# Gemini Author Notes \u2014 Turn 15 (In Progress)\n\n## 1. Protocol & Hardware State (Record `0060`)\n[line removed by the dashboard scrubber]\n- **GPU 0 Unavailable**: Held all turn by `cf001-p0` (`94.7 / 97.9 GiB`). No CPU or second-GPU path exists for `vgen.py` rollout checks while GPU 0 runs `cf001`; pre-testing uses exact layer-by-layer CPU `g31` (`mirror=True`) on strictly unseen `safe_s1` episodes (`closeprobe` + `delimprobe` + phase-stratified KL/flip vs empirical anchors `0044` and `0055`).\n\n## 2. Turn-12 (`x009`) Forensic Autopsy vs Turn-9 (`x006`)\n[line removed by the dashboard scrubber]\n- **Why `0044` (`dual-audit-postedit-boost`, `+5.5`) succeeded**: **100% of its gain came on the `87` strictly unseen non-fit tasks (`+5.5` raw = `+7.6 / 120` unseen; `+0.0` on `32` fit tasks)**, preserving `100%` of codebase reading (`read_file = 8.0 vs 8.0`) with zero `WRONG_CLEAN` regressions on `68` reliable (`12..14/14`) tasks. Its only structural defects were `69.7%` small-`w_post` blowup at `11.down_proj` and `+20%` unconditional thought lengthening (`pipdeptree-488` cutoff).\n- **Why `0056` (`tri-phase-concise-audit-veto`, `-1.5`, `80/119`) regressed**:\n[... 50 lines cut ...]\n[line removed by the dashboard scrubber]\n8\n4assert words < 600, f\"NOTES too long: {words} words\"\n:\n6NOTES_PATH.write_text(INTERIM_NOTES, encoding=\"utf-8\")\n<\n8print(f\"Updated interim NOTES.md ({words} words < 600)\")\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/200/output.txt"},{"i":201,"kind":"raw","long":false,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\package_t15.py C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\write_notes_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/write_notes_t15.py'\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Upload package_t15 and update interim NOTES.md\"}2\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\package_t15.py C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\write_notes_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/write_notes_t15.py'\n.Upload package_t15 and update interim NOTES.md\nCreated At: 2026-11-14T15:32:08-05:00\nCompleted At: 2026-11-14T15:32:13-05:00\nCommand exited with code 0.\n\nCommand output:\nUpdated interim NOTES.md (486 words < 600)\nterminalJ0\n.upload package_t15 and update interim NOTES.mdR\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\package_t15.py C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\write_notes_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/write_notes_t15.py'\n\"+Updated interim NOTES.md (486 words < 600)\n2\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\package_t15.py C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\write_notes_t15.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/; ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gemini/code/write_notes_t15.py':%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/201/output.txt"},{"i":202,"kind":"raw","long":false,"text":":(bot-cf9a6f71-7c1a-4fb6-add8-c5bea20c43cdB!\n\tsessionID\nInspecting the task's progress, preparing to finalize entries once pre-test data becomes available. Developing a local script to process the pre-test report. The script will allow examination of pre-test numbers from a JSON output.\n\n\nAnalyzing the pre-test report data from the JSON output to compare several metrics across control arms. The script `finalize_t15_entries.py` automatically selects optimal doses, packages the entries and updates records according to existing guidelines. The process will verify each detail in `record.md` for Entry 1 and Entry 2, in accordance with other documentation.\n\n\nExamining the generated titles, both meet the character limit and avoid disallowed characters. The hypothesis section now explicitly references the baseline performance of the unedited run, highlighting improvements over prior versions by referencing specific changes in performance metrics across tasks, especially on unseen tasks and certain tasks like `read_file`. The focus now shifts to analyzing the impact on specific task categories and failure modes to understand performance limitations.\n\n\nAnalyzing results from the latest tests. Adding a focus prompt to one neuron slashed performance on `read_file` tasks and reduced reliability. Another neuron with a submit veto achieved the lowest failure rate. Purging the focus prompt entirely seems to be the best path forward, focusing on neurons with existing performance metrics.\n\n\nEntry 2 (\"debiased-oproj-postveto-r6\") presents a complex interplay of factors impacting performance. The initial focus was on addressing specific failure modes in tasks like `read_file`. Analysis revealed that the `focus_all` prompt had significant negative consequences, particularly in slashing performance on `read_file`.\n\nThe debiased entry integrates complementary Attention + MLP mechanisms, utilizing a large number of disjoint matrices to counteract these issues. This approach is designed to overcome limitations observed in previous configurations. The current goal is to ensure this revised architecture is robust across varied tasks and failure scenarios.\n\n\nFocusing on the architectural revisions, the entry incorporates a debiased post-veto design with specific matrix adjustments and routing layer weighting. The updated MLP omits pre-edit context routing from the original `j_0`, utilizing specific GeGLU phase gates for auditing and verification. The approach builds on a champion generation baseline with size and control size parameters specified.\n\n\nExamining the specific episodes and their labels, confirming the pre-test numbers for unseen scenarios. These are directly compared against baseline references, matched against control groups. Tool verifications are explicitly noted, with particular attention to GPU versus CPU implementations and their current verification status.\n\n\n2(bot-cf9a6f71-7c1a-4fb6-add8-c5bea20c43cd:\n[line removed by the dashboard scrubber]"},{"i":203,"kind":"raw","long":true,"text":"[line removed by the dashboard scrubber]\n#!/usr/bin/env python3\n\"\"\"Turn 15 complete deterministic CPU finalizer (author: gemini):\n1. Packages Entry 1 (`pure-audit-postedit-veto-r3`, r=3, 180 MLP matrices) completely through `READY` FIRST,\n and updates `NOTES.md`.\n2. Packages Entry 2 (`debiased-oproj-postveto-r6`, r=6, 230 disjoint Attention+MLP matrices) completely through `READY` SECOND,\n cleans temporary scratch files, and writes final `NOTES.md` (< 600 words).\n\"\"\"\nimport argparse\nimport json\nimport pathlib\nimport shutil\nimport sys\n\nimport torch\n\nR = pathlib.Path(\"/home/keith/gemma-v2\")\nME = R / \"wsp31/authors/gemini\"\nCODE = ME / \"code\"\nSCR = ME / \"scratch\"\n[... 516 lines cut ...]\n- **Why `0055` (`-3.5`, `78/119`) overdosed yet cut cutoffs `-90.5%`**: `16.8%` `L5..24` `o_proj` stream energy along `focus_all`, overfit `L20..58` `down_proj` ridge (`r2_oof = 0.0009`, `pres_ratio = 39.5`), and unweighted 54-layer compounding (`-58%` `read_file`, `+14` unseen `WRONG_CLEAN`) masked genuine early global/local `o_proj` routing (`L5, L11` `r2_oof = 0.113`) that cut unseen `CUT+EMP` `10.5 -> 1`.\nI\nE## 3. Turn-15 Queued Entries (Both `READY`, CPU-Deterministic `< 6s`)\n1. **`{slug1}`** (`{se1['net_rel']*100:.2f}%` over `180` MLP matrices `0..59`, `r=3`, max `{se1['rel_max']*100:.2f}%`, pred `+3.0 to +8.0`): Purges `P_focus` 100%; pairs `t9.comp_thought_quad`+`t9.audit_all` (`dose={cfg1['dose_all']}`), `t12.post_thought`+uncontaminated `t9.audit_post` (`dose={cfg1['dose_post']}`), and `t12.submit_veto`+`focus_all`-orthogonalized `veto_submit` (`dose={cfg1['dose_veto']}`). Unseen pre-test: `d_close = {ev1['cp_d_close']:+.4f}`, `delim_err = {ev1['dp_delim_err']:.3f}`, `flip_th = {ev1['flip_th_all']*100:.1f}%`, `d_sub = {ev1['d_sub_vs_verify']:+.4f}`.\n2. **`{slug2}`** (`{se2['net_rel']*100:.2f}%` over `230` disjoint matrices: `50` `o_proj` `5..54` + `180` MLP `0..59`, `r=6`, max `{se2['rel_max']*100:.2f}%`, pred `+2.5 to +7.5`): Exact stream-space `focus_all`-debiased, `r2_oof`-weighted `o_proj` (`{cfg2['target_oproj_net_rel']*100:.2f}%` norm, `down_proj` ridge dropped) + 2-neuron (`j_1, j_2`) MLP controller (no `j_0`). Unseen pre-test: `d_close = {ev2['cp_d_close']:+.4f}`, `delim_err = {ev2['dp_delim_err']:.3f}`, `flip_th = {ev2['flip_th_all']*100:.1f}%`, `d_sub = {ev2['d_sub_vs_verify']:+.4f}`.\nT\nP print(\"\\n=== ALL TURN-15 PACKAGING & VERIFICATION COMPLETE ===\", flush=True)\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/203/output.txt"},{"i":204,"kind":"raw","long":false,"text":":(bot-af44f0d7-f5a4-409e-a7f7-c73a484bb39aB!\n\tsessionID\nThe script `finalize_t15_entries.py` needs to be copied to `wrx90`. The process will check `task-194.log` using `read_file`. It will wait for the task to complete, then report the status if it's still running.\n\n\n2(bot-af44f0d7-f5a4-409e-a7f7-c73a484bb39a:\n{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\finalize_t15_entries.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/finalize_t15_entries.py\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Upload finalize_t15_entries.py to wrx90\"}:\n{\"Path\":\"C:\\\\Users\\\\Owner\\\\.gemini\\\\antigravity-cli\\\\brain\\\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\\\.system_generated\\\\tasks\\\\task-194.log\"}Z"},{"i":205,"kind":"raw","long":false,"text":"{\"CommandLine\":\"scp -q C:\\\\Users\\\\Owner\\\\wsp31_loop\\\\work\\\\gemini\\\\finalize_t15_entries.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/finalize_t15_entries.py\",\"WaitMsBeforeAsync\":10000,\"toolSummary\":\"Upload finalize_t15_entries.py to wrx90\"}:\n'Upload finalize_t15_entries.py to wrx90\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\finalize_t15_entries.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/finalize_t15_entries.py\nCreated At: 2026-11-14T15:34:40-05:00\nCompleted At: 2026-11-14T15:34:43-05:00\nCommand exited with code 0.\n\nNo output from the command.\nterminalJ)\n'upload finalize_t15_entries.py to wrx90R\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\finalize_t15_entries.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/finalize_t15_entries.py\n4type.googleapis.com/exa.cortex.core.tools.RunCommand\nscp -q C:\\Users\\Owner\\wsp31_loop\\work\\gemini\\finalize_t15_entries.py wrx90:/home/keith/gemma-v2/wsp31/authors/gemini/code/finalize_t15_entries.py:%C:\\Users\\Owner\\wsp31_loop\\work\\gemini:\nfile:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/steps/205/output.txt"},{"i":206,"kind":"raw","long":false,"text":"{\"Path\":\"C:\\\\Users\\\\Owner\\\\.gemini\\\\antigravity-cli\\\\brain\\\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\\\.system_generated\\\\tasks\\\\task-194.log\"}2\nvC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\tasks\\task-194.log\nCreated At: 2026-11-14T15:34:40-05:00\nCompleted At: 2026-11-14T15:34:43-05:00\nShowing lines 1-12 of 12\n[line removed by the dashboard scrubber]\n2: [pre_edit ] [task] call= 1 n=2910 cp=3 dp=11 sub=0\n3: [pre_edit ] jsvine__pdfplumber.02ff4313.func_pm_remove_assign__1v9soh1j call= 2 n=3339 cp=2 dp=11 sub=0\n4: [post_edit] [task] call=21 n=3005 cp=2 dp=11 sub=0\n5: [post_edit] [task] call=41 n=3359 cp=4 dp=7 sub=0\n6: [pre_sub ] [task] call=14 n=5109 cp=2 dp=7 sub=1\n7: [pre_sub ] django-money__django-money.835c1ab8.combine_module__bqggrnha call=18 n=5504 cp=2 dp=7 sub=1\n8: Built e1_m: r=3 changed=180 edit_net=1.2881% ctrl_net=1.2881% max_mat=6.54%\n9: Built e1_s: r=3 changed=180 edit_net=1.3099% ctrl_net=1.3099% max_mat=7.43%\n10: Built e2_m: r=6 changed=230 edit_net=1.1413% ctrl_net=1.1413% max_mat=6.41%\n11: Built e2_s: r=6 changed=230 edit_net=1.1816% ctrl_net=1.1816% max_mat=7.04%\n12: [215.9s] Bit-for-bit Layer-0 check vs G31.forward(mirror=True): max_abs_diff=0.00000000\n~file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-194.log\n2type.googleapis.com/exa.cortex.core.tools.ReadFile\nvC:\\Users\\Owner\\.gemini\\antigravity-cli\\brain\\4fbddbc5-e478-44c0-a42f-2366c93d8394\\.system_generated\\tasks\\task-194.log"},{"i":207,"kind":"raw","long":false,"text":":(bot-cfcf5002-f868-49fc-866c-c32e179c1643B!\n\tsessionID\nLaunched the exact batched 60-layer CPU `g31` (`mirror=True`) pre-test battery ([t15_cpu_pretest.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/t15_cpu_pretest.py)) on `wrx90` across 6 strictly unseen Stage-1-only episodes (verified `max_abs_diff = 0.00000000` against `G31.forward`), with [t15_build.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/t15_build.py), [package_t15.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/package_t15.py), [finalize_t15_entries.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/finalize_t15_entries.py), and interim `NOTES.md` staged. Waiting for the pre-test task to finish before selecting final doses and packaging both queue entries (`READY`).\nLayer-0 bit-for-bit check passes, indicating no discrepancy at that stage. This confirms the initial hypothesis regarding Layer-0 integrity. The timing discrepancy between the original test (0.2s) and the current check (215.9s) for Layer 0 points to processing differences before that point, specifically in the setup related to `m.forward(test_ids, stop_after=0)`.\n\n\n2(bot-cfcf5002-f868-49fc-866c-c32e179c1643B\nLaunched the exact batched 60-layer CPU `g31` (`mirror=True`) pre-test battery ([t15_cpu_pretest.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/t15_cpu_pretest.py)) on `wrx90` across 6 strictly unseen Stage-1-only episodes (verified `max_abs_diff = 0.00000000` against `G31.forward`), with [t15_build.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/t15_build.py), [package_t15.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/package_t15.py), [finalize_t15_entries.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/finalize_t15_entries.py), and interim `NOTES.md` staged. Waiting for the pre-test task to finish before selecting final doses and packaging both queue entries (`READY`).Z"},{"i":208,"kind":"raw","long":true,"text":"[Message] timestamp=2026-11-14T21:35:35Z sender=4fbddbc5-e478-44c0-a42f-2366c93d8394/task-194 priority=MESSAGE_PRIORITY_HIGH content=Task id \"4fbddbc5-e478-44c0-a42f-2366c93d8394/task-194\" finished with result:\nCommand exited with code 1.\n\nCommand output:\n[line removed by the dashboard scrubber]\n [pre_edit ] [task] call= 1 n=2910 cp=3 dp=11 sub=0\n [pre_edit ] jsvine__pdfplumber.02ff4313.func_pm_remove_assign__1v9soh1j call= 2 n=3339 cp=2 dp=11 sub=0\n [post_edit] [task] call=21 n=3005 cp=2 dp=11 sub=0\n [post_edit] [task] call=41 n=3359 cp=4 dp=7 sub=0\n [pre_sub ] [task] call=14 n=5109 cp=2 dp=7 sub=1\n [pre_sub ] django-money__django-money.835c1ab8.combine_module__bqggrnha call=18 n=5504 cp=2 dp=7 sub=1\n Built e1_m: r=3 changed=180 edit_net=1.2881% ctrl_net=1.2881% max_mat=6.54%\n Built e1_s: r=3 changed=180 edit_net=1.3099% ctrl_net=1.3099% max_mat=7.43%\n Built e2_m: r=6 changed=230 edit_net=1.1413% ctrl_net=1.1413% max_mat=6.41%\n Built e2_s: r=6 changed=230 edit_net=1.1816% ctrl_net=1.1816% max_mat=7.04%\n[215.9s] Bit-for-bit Layer-0 check vs G31.forward(mirror=True): max_abs_diff=0.00000000\n Layer 00/59 done in 124.90s (elapsed 124.9s)\n Layer 05/59 done in 114.69s (elapsed 638.2s)\n Layer 11/59 done in 115.62s (elapsed 1158.0s)\n Layer 19/59 done in 79.57s (elapsed 1832.3s)\n[... 45 lines cut ...]\n Layer 00/59 done in 124.90s (elapsed 124.9s)\n Layer 05/59 done in 114.69s (elapsed 638.2s)\n Layer 11/59 done in 115.62s (elapsed 1158.0s)\n Layer 19/59 done in 79.57s (elapsed 1832.3s)\n Layer 29/59 done in 116.72s (elapsed 2703.4s)\n Layer 39/59 done in 82.30s (elapsed 3541.2s)\n\nLog: file:///C:/Users/Owner/.gemini/antigravity-cli/brain/4fbddbc5-e478-44c0-a42f-2366c93d8394/.system_generated/tasks/task-194.log"},{"i":209,"kind":"raw","long":false,"text":"Captured output of the turn:\nroot agent idle; waiting for 1 background task(s) to finish\nLaunched the exact batched 60-layer CPU `g31` (`mirror=True`) pre-test battery ([t15_cpu_pretest.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/t15_cpu_pretest.py)) on `wrx90` across 6 strictly unseen Stage-1-only episodes (verified `max_abs_diff = 0.00000000` against `G31.forward`), with [t15_build.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/t15_build.py), [package_t15.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/package_t15.py), [finalize_t15_entries.py](file:///C:/Users/Owner/wsp31_loop/work/gemini/finalize_t15_entries.py), and interim `NOTES.md` staged. Waiting for the pre-test task to finish before selecting final doses and packaging both queue entries (`READY`)."}],"updated":"2026-11-15T02:05:46Z"}