{"chunks":1,"id":"t010","last_seq":0,"rows":[{"i":0,"kind":"meta","long":false,"text":"Reading additional input from stdin...\nOpenAI Codex v0.155.1\n--------\nworkdir: C:\\Users\\Owner\\wsp31_loop\\work\\gpt\nmodel: gpt-6-astra\nprovider: openai\napproval: never\nsandbox: danger-full-access\nreasoning effort: high\nreasoning summaries: concise\nsession id: 01a1da5c-098a-7072-ba67-715136009ed9\n--------"},{"i":1,"kind":"user","long":false,"text":"You are author 'gpt' in the wsp31 weight-editing programme. This is turn 10. 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 'gpt' (your directory is /home/keith/gemma-v2/wsp31/authors/gpt/). The results of your last round, and every other author's entries and results, are in /home/keith/gemma-v2/wsp31/authors/gpt/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."},{"i":2,"kind":"assistant","long":false,"text":"I\u2019ll read the brief and results on wrx90, then complete one round as author `gpt` within the two-entry limit."},{"i":3,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/BRIEF.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":4,"kind":"output","long":true,"text":" succeeded in 249ms:\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\ntwo entries per round and then wait for their results, so each one counts; a third variation of a null result is a\nwasted round. High-risk ideas with a clear mechanism and a\nprediction that could be wrong are what this programme wants. Say what would prove you wrong.\n\n## Where you work\n\n- Everything happens on host `wrx90`, reached with `ssh -o BatchMode=yes wrx90 '<command>'`. Write scripts in your\n  local working directory, copy them with `scp`, run them with ssh. Keep ssh output small (`tail`, `cut`, `head`).\n- Root: `/home/keith/gemma-v2` (below: `$R`). Python: `$R/tii-venv/bin/python` (torch, transformers, vLLM 0.19.1,\n[... 207 lines cut ...]\n- An edit that passes both stages is promoted: it becomes part of the champion for everything after it.\n- The champion is confirmed on tasks you do not see, against the unedited model, and the final champion gets one\n  pre-registered held-out run. A changed edit is a new edit.\n- A combination of your own edits is a new queue entry with its own record, prediction and control. Combining with\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."},{"i":5,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md; cat /home/keith/gemma-v2/wsp31/authors/gpt/RESULTS.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":6,"kind":"output","long":true,"text":" succeeded in 261ms:\n# Author gpt \u2014 turn 7, queued-s1-0035-and-0036\n\nUpdated 2026-11-14T05:18:54.043693+00:00. Started 03:54 UTC; hard turn deadline 05:24 UTC, 14 Nov 2026. Champion generation 0 at design. One round, at most two entries.\n\nPrevious results: 0011/0012 harmful; 0025/0026 code-style writer damping null (-1 and 0 tasks against mean reference). Do not repeat close amplification. Parked 0013/0027 remain parked. Prior notes: code/turn7/previous_notes.md.\n\n[line removed by the dashboard scrubber]\n\nCPU audit: 208 b007 reference episodes from the 104 tasks shared by both stage-1 lists. Edit replies: 244 OK, 32 error, 57 missing; missing is not success. Only 9 immediate identical retries after 488 error replies, so retry suppression alone has a small ceiling. The main target is fewer incorrect edits and better use of tool evidence. The borgbackup example reconstructs source in thought then fails old_string matching.\n\n[line removed by the dashboard scrubber]\n\n[line removed by the dashboard scrubber]\n\n[line removed by the dashboard scrubber]\n\nSubmitted this turn: source-grounding-icv-b3, source-grounding-icv-b1.\nGPU usage: zero seconds; never acquired the lock.\n\n[... 68 lines cut ...]\n| 0023 | claude | net-preedit-commit-close-b05 | Pre-edit rumination gate in all 60 layers: deep in a thought with no edit made yet, write end-of-thought plus first-edit state (per-layer do | parked | -8 to +9 |  |  | - |\n| 0028 new | gemini | nullspace-close-r4-midlate | Protocol-nullspace rank-4 exact thought-close writer subspace across L10-59 (0.48%) | done | +1 to +13 | -10.5 (62 vs 73) |  | harmful |\n| 0031 new | claude | icv-brief-b20 | Instruction vector, think briefly: an always-on neuron per layer writes the stream shift of a 'keep your thinking short' paragraph (dose 2) | done | -6 to +6 | +9.0 (77 vs 72) | +10.5 (control +6.5) provisional | null |\n| 0032 new | claude | icv-brief-b40 | Instruction vector, think briefly: an always-on neuron per layer writes the stream shift of a 'keep your thinking short' paragraph (dose 4) | running_s2 | -9 to +6 | +3.0 (71 vs 72) |  | - |\n| 0038 new | claude | fcv-brief-b20 | Think-briefly instruction vector, self-consistent compile (dose 2): each layer writes only what the paragraph's mean shift still lacks | done | -2 to +8 | -2.0 (75 vs 78) |  | null |\n| 0039 new | 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) | done | -4 to +8 | +2.0 (79 vs 78) |  | null |\n| 0043 | gemini | spec-audit-thought-gate | Thought-gated reliability-shrunk Problem Statement spec-audit steering across all 60 MLP layers | queued_s1 | +2 to +7 |  |  | - |\n| 0044 | gemini | dual-audit-postedit-boost | Stateful two-neuron post-edit spec-audit boost with thought and edit-history gating over 180 MLP matrices | queued_s1 | +3 to +8.5 |  |  | - |"},{"i":7,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"rg -n \\\"wsp31|weight.editing\\\" C:\\\\Users\\\\Owner\\\\.codex\\\\memories\\\\MEMORY.md\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":8,"kind":"output","long":false,"text":" exited 1 in 15ms:"},{"i":9,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/queue/STATUS.md; cat /home/keith/gemma-v2/wsp31/queue/CHAMPION.md; cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/LEDGER.md; ls /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/ledger'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":10,"kind":"output","long":true,"text":" succeeded in 243ms:\n# wsp31 queue status (2026-11-14 09:00:17 EST)\n\nRule: {\"s1_promote\": 3.0, \"s1_harmful\": -6.0, \"s2_min\": 4.0, \"ctrl_margin\": 5.0, \"total_pass\": 10.0, \"total_harmful\": -10.0}\n\nChampion (the base every new edit is scored against): Generation 0: the unedited model. No edit has passed yet.\n\nReference arms of a new batch: the unedited model served through an all-zero adapter, the same serving path as an edit (ledger record 0033).\n\n[line removed by the dashboard scrubber]\n\n## Batches\n\n| batch | stage | gpu | state | arms | rows | note |\n|---|---|---|---|---|---|---|\n| b001-supp1 | s1 | 1 | done | base aa zero | 93 | {\"tasks\": 31, \"record\": \"0030\", \"solved\": {\"base\": [60, 74], \"aa\": [60, 74], \"zero\": [65, 81]}} |\n| b006 | s2 | 1 | done | base e0015 c0015 aa | 872 | {\"base\": 121, \"episodes\": 218, \"aa\": [121, 110, 24, 13], \"arms\": {\"e0015\": [119, 3.5], \"c0015\": [112, -3.5]}} |\n| b007 | s1 | 0 | done | base e0025 e0026 aa | 480 | {\"base\": 65, \"episodes\": 120, \"aa\": [65, 73, 4, 12], \"arms\": {\"e0025\": [68, -1.0], \"e0026\": [69, 0.0]}} |\n| x001 | s1 | box | done | base e0031 e0032 aa |  | {\"base\": 72, \"episodes\": 120, \"aa\": [72, 64, 13, 5], \"arms\": {\"e0031\": [77, 9.0], \"e0032\": [71, 3.0]}} |\n| x002 | s1 | box | done | base e0028 e0016 aa | 480 | {\"base\": 73, \"episodes\": 120, \"aa\": [73, 72, 6, 5], \"arms\": {\"e0028\": [62, -10.5], \"e0016\": [73, 0.5]}} |\n[... 165 lines cut ...]\n0038-claude-fcv-brief-b20.md\n0039-claude-fcv-brief-exact-b20.md\n0040-claude-episode-budget-20000.md\n0041-claude-correction-b002-supp1.md\n0042-claude-correction-b004-supp1.md\n0043-gemini-spec-audit-thought-gate.md\n0044-gemini-dual-audit-postedit-boost.md\nTEMPLATE.md"},{"i":11,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/PRIOR_E4B.md; cat /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md; cat /home/keith/gemma-v2/wsp31/tools/TOOLS.md; cat /home/keith/gemma-v2/wsp31/tools/ARCH.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":12,"kind":"output","long":true,"text":" succeeded in 266ms:\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\nA frontier LLM diagnosed failures from logged agent decisions, located a direction in the residual stream (difference\nof means between decision classes), compiled it into a closed-form MLP edit (always-on, or gated by a \"quiet neuron\"\nthat fires only under a condition such as \"no file edited yet\"), wrote a prediction, and tested against a\nnorm-matched random control.\n\n## What moved behaviour\n\n[... 759 lines cut ...]\n[line removed by the dashboard scrubber]\n|---|---|---|\n| `turn` | newline after `<|turn>model` | think first (`<|channel>`) or call a tool at once |\n| `step` | `<tool_response|>` that closes a tool result | think, call another tool, or answer in text |\n| `think` | `<channel|>` that closes a thought | call a tool or write text |\n[line removed by the dashboard scrubber]\n\n**Fetching files locally**"},{"i":13,"kind":"assistant","long":false,"text":"[line removed by the dashboard scrubber]"},{"i":14,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/TOOLS.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":15,"kind":"output","long":true,"text":" succeeded in 232ms:\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\nEverything here lives in `$R/wsp31/tools` (below `$T`; `$R = /home/keith/gemma-v2`). Each entry ends with\n**Verified by** (a measurement that was made) or **NOT VERIFIED YET** (written, first real run still queued; use it,\nbut do not build a claim on its numbers alone). Architecture facts are in `$T/ARCH.md` (read \"Consequences for\nweight edits\" there before designing an edit); measurements with commands are in `$T/REPORT.md`.\n\n    . /home/keith/gemma-v2/env.sh; T=$R/wsp31/tools\n    export WSP31_WORK=$R/wsp31/authors/<you>/scratch     # caches and server logs of the tools go here, not into $T\n\n[... 287 lines cut ...]\n\n## 8. Not available yet\n\n[line removed by the dashboard scrubber]\n- Activation atlas and its views; `--champion` runs of `dose.py`, `validate.py`, `closeprobe.py`, `vgen.py`.\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)."},{"i":16,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'sed -n \\\"/\"'^## C'\"\\\\./,/\"'^## D'\"\\\\./p\\\" /home/keith/gemma-v2/tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md; head -180 /home/keith/gemma-v2/wsp31/interp/REPORT.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":17,"kind":"output","long":true,"text":" succeeded in 231ms:\nsed: -e expression #1, char 4: unterminated address regex\n# Interpretability lane: what is known about the inside of Gemma 4 31B\n\n[line removed by the dashboard scrubber]\nown runs; anything else is labelled. Pre-registration: `PROTOCOL.md` (sections 0-5 and dated amendments 1, 2, 3, 3a,\n3b, 3c, 3d, 3e, 3f, 3g, 3h, 3i, 3j, 3k, 4, 4a, 4b, 5, 5a, 5b, 5c, 5d, 5e). Located-and-causally-checked components: `ATLAS.md` (one entry since 1:06 AM ET, Fri 13 Nov: the close-the-thought direction). Lens-only readings:\n`ATLAS_lens.md`.\n\n[line removed by the dashboard scrubber]\n\nThe author brief points to this block. It is kept current and can be read alone; the dated blocks below it are\nthe record. All screening numbers here are stage 1 unless stage 2 is named, one rollout per task and arm: 120 tasks in b002 and b003, 102\n[line removed by the dashboard scrubber]\n\n- **New (8:57 AM ET, Sat 14 Nov 2026): 0009 (claude; the model's own end-of-thought neurons at 25 times their write) is harmful: 3 of 120\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n  stage 1, the same 120 tasks, budget 20,000, one rollout per task). Both carried predictions this lane registered in\n  advance (amendment 5): 1 of 4 mechanism predictions hit, and the outcome prediction for 0007 missed by one task.**\n[... 156 lines cut ...]\n    against both unedited arms, and for solved tasks it does not. Stage 2 is queued for both.\n  - Twice the dose removed more cut-offs and did not solve more: 0032 against 0031 lost 10 and gained 4 (p 0.18,\n    not a shown difference). In the 35 tasks cut off in both unedited arms, 0031 is not cut off in 10 and 0032 in\n    23, and each solves 12 (the unedited arms 9 and 9). Of the 59 tasks both unedited arms solve, 0031 solves 56\n    and 0032 53. Episodes with an empty patch: 21 | 18 | 13 | 8.\n  - No sign of broken tool-call syntax in the traces: `read_file` calls that fail on the path 5 | 12 | 2 | 3 (74\n\n**Considering improved quantization and testing**"},{"i":18,"kind":"tool","long":false,"text":"[line removed by the dashboard scrubber]"},{"i":19,"kind":"output","long":true,"text":" succeeded in 257ms:\nsed: -e expression #1, char 4: unterminated address regex\n[line removed by the dashboard scrubber]\nbash: line 1: minutes: command not found\nbash: line 1: seconds: command not found\n/home/keith/gemma-v2/wsp31/authors/gpt/code/close033_record.json\n/home/keith/gemma-v2/wsp31/authors/gpt/code/audit_boundary.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/author_capture.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/build_project.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/audit_snapshot.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/non_split.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/probe_job.sh\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/environment.json\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/prepare_closecheck.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/cpu_ground_stats.pt\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/write_record.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/gpu_dispatch.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/hold2.sh\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/provenance.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/audit_calls.py\n[... 141 lines cut ...]\n/home/keith/gemma-v2/wsp31/authors/gpt/code/cancel_optional.py\n/home/keith/gemma-v2/wsp31/authors/gpt/code/capture_job.sh\n3.6G\t/home/keith/gemma-v2/wsp31/authors/gpt/scratch\n               total        used        free      shared  buff/cache   available\nMem:             183          17          88           0          80         166\nSwap:              7           1           6\n\n**Managing script quoting and patching**"},{"i":20,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"Get-Location; rg --files -g AGENTS.md -g '*.py' -g '*.sh'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":21,"kind":"output","long":true,"text":" succeeded in 40ms:\n\nverify_rebuild.py\nupdate_frozen_manifest.py\nturn7\\write_record.py\nturn7\\update_notes.py\nturn7\\trace_schema.py\nturn7\\thinklib.py\nturn7\\stop_own.py\nturn7\\setup_remote.py\nturn7\\select_final.py\nturn7\\replay_cpu.py\nturn7\\replay_after_capture.sh\nturn7\\repeat_audit.py\nturn7\\recovery_audit.py\nturn7\\read_ledgers.py\nturn7\\ready.py\nturn7\\provenance.py\nturn7\\progress.py\nturn7\\prepare_cpu.py\n[... 83 lines cut ...]\naudit_snapshot.py\naudit_boundary.py\nafter_capture.sh\nPath                              \n----                              \nC:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":22,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/ground_job.py /home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/build_ground.py /home/keith/gemma-v2/wsp31/authors/gpt/code/turn7/ground_gen.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":23,"kind":"output","long":true,"text":" succeeded in 237ms:\n\"\"\"icv_job.py (author gpt, turn 7; adapted from claude turn 6): one GPU-0 hold with tools/g31.py (forward pass only, no server).\n\nInstruction vectors compiled into the weights as an always-on MLP neuron in every layer.\n  1. capture: for stage-1 calls of the unedited b001 arms, run the logged call (prompt + the completion the agent\n     wrote) once as logged and once with an instruction paragraph inserted at the end of the first user message.\n     d_L[I] = mean over calls of mean over completion positions of resid_post_L(with I) - resid_post_L(without).\n  2. per layer the part layer L adds itself: delta_L = d_L - layer_scalar_L * d_{L-1}  (d_{-1} = 0).\n  3. in every layer one quiet MLP neuron is replaced (\"set\") by an always-on neuron: gate row K w, up row w, with\n     w . x = 1 on average over completion positions (x = MLP input), so its activation is about K at every position;\n     its down column writes beta * delta_L into the stream (through the post-feedforward norm and layer_scalar).\n  4. teacher-forced evaluation on held-out tasks: base, prompted with I, and each arm, on the logged completion.\n`--mock` runs the whole script on CPU with random activations (plumbing test).\n\"\"\"\nimport json\nimport math\nimport os\nimport random\nimport sys\nimport time\n[... 607 lines cut ...]\n+print('LATEST RESULTS SCHEMA')\n+for arm in ['base','aa']:\n+ ps=list((R/f'results/wsp31/batches/x004/{arm}').rglob('task_results.jsonl'))\n+ for p in ps[:1]:\n+  rows=[json.loads(l) for l in p.open()];print(str(p),len(rows),rows[0])\n+  fail=[x for x in rows if not x.get('resolved') and not x.get('agent_error')]\n+  print('FAIL',[(x.get('instance_id'),x.get('patch_chars'),x.get('tool_calls')) for x in fail[:10]])\n+(A/'NOTES.md').write_text('# Author gpt - turn 10 in progress\\n\\nStarted 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Prior source-grounding ICV doses 3 and 1 were null (-2.5/-3.5). Do not repeat closing-thought or constant source-grounding edits. Reading latest stage-1 failures and choosing a new mechanism. No entries submitted yet; maximum two. GPU budget 2700 seconds, none used.\\n')"},{"i":24,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/inspect.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/inspect_turn10.py' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":25,"kind":"output","long":false,"text":" succeeded in 329ms:"},{"i":26,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/inspect_turn10.py > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/inspect_turn10.txt'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":27,"kind":"output","long":false,"text":" succeeded in 231ms:"},{"i":28,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/scratch/inspect_turn10.txt turn10/inspection.txt' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":29,"kind":"output","long":true,"text":" succeeded in 263ms:\ndiff --git a/turn10/inspect.py b/turn10/inspect.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..af7e4eaaf226ec36a85c1bf73e83173e545ec8f4\n--- /dev/null\n+++ b/turn10/inspect.py\n@@ -0,0 +1,26 @@\n+from pathlib import Path\n+import json,re\n+R=Path('/home/keith/gemma-v2'); A=R/'wsp31/authors/gpt'; C=A/'code/turn10'; S=A/'scratch/turn10'\n+C.mkdir(exist_ok=True); S.mkdir(exist_ok=True)\n+survey=(R/'tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md').read_text()\n+print(survey[survey.index('## C.'):survey.index('## D.')])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines()\n+for i,l in enumerate(rep):\n[line removed by the dashboard scrubber]\n+  if i<400: print('\\n'.join(rep[max(0,i-2):i+12]))\n+print('LEDGER RECIPES')\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0025','0031','0035','0038','0039','0043','0044']:\n[... 5 lines cut ...]\n+print('LATEST RESULTS SCHEMA')\n+for arm in ['base','aa']:\n+ ps=list((R/f'results/wsp31/batches/x004/{arm}').rglob('task_results.jsonl'))\n+ for p in ps[:1]:\n+  rows=[json.loads(l) for l in p.open()];print(str(p),len(rows),rows[0])\n+  fail=[x for x in rows if not x.get('resolved') and not x.get('agent_error')]\n+  print('FAIL',[(x.get('instance_id'),x.get('patch_chars'),x.get('tool_calls')) for x in fail[:10]])\n+(A/'NOTES.md').write_text('# Author gpt - turn 10 in progress\\n\\nStarted 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Prior source-grounding ICV doses 3 and 1 were null (-2.5/-3.5). Do not repeat closing-thought or constant source-grounding edits. Reading latest stage-1 failures and choosing a new mechanism. No entries submitted yet; maximum two. GPU budget 2700 seconds, none used.\\n')"},{"i":30,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'Get-Content turn10/inspection.txt -TotalCount 75; Get-Content turn10/inspection.txt -Tail 160' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":31,"kind":"output","long":true,"text":" succeeded in 50ms:\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 `<channel\\|>` (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 \u00e2\u2030\u00a40) | 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| 4 | **Spectrally filtered donor delta.** Take community gemma-4-31B-it agentic-coding LoRAs. Keep each matrix's dominant singular directions, Frobenius-match magnitude, and DARE/TIES-merge several. Treat the dose \u00ce\u00b1 as a hyperparameter | Selective-RL (controls beat magnitude-only and random low-rank); fine-tuning transfer; DARE/TIES | Donor LoRAs (verify licence, data, contamination); none are RL-trained | Medium\u00e2\u20ac\u201chigh. Unknown donor quality. Note: this imports someone else's training, so it is \"training-free for us\" and may need to be reported separately from \"LLM-authored\" |\n| 5 | **Head-level cognitive edits (CREST/ThinkEdit style).** Find heads whose outputs separate productive from unproductive verification and backtracking (or premature \"submit\"); remove or add the component in those heads' o_proj | CREST (up to +17.5%); ThinkEdit (0.2% of params, +3.34%) | Per-head activations at labelled step types | Medium. Shown on math reasoning, not agents |\n| 6 | **Verification / tool-use direction.** One residual direction raising the rate of \"run tests / inspect output\" actions, dosed in the agent loop | Tool-call rates (0\u00e2\u2020\u201990%; QA 0.29\u00e2\u2020\u20190.56); TACT's overacting axis as the counterweight | Contrast of states before tool-call vs no-tool turns | Medium. Too much dose means more steps or timeouts. Pair with idea 1's OA axis |\n| 7 | **RYS middle-block duplication.** Materialise a 61\u00e2\u20ac\u201c68-layer checkpoint that repeats a contiguous mid block; search (i, j) on dev agent tasks or a proxy (teacher-forced NLL on successful trajectories, plus LCB) | RYS on Qwen3.5-27B | Proxy sweep (cheap), then agent evals | Medium\u00e2\u20ac\u201chigh. Weak evidence; adds KV cache; counts as an architecture edit for framing |\n| 8 | **Agency-axis nudge at prefill**, so the agent acts rather than defers or stalls (relevant if traces show hedging or asking for confirmation) | Agency axis (d=1.01; decode-only had no effect) | Contrast \"acts\" vs \"asks or stalls\" turns | Medium. Risk of reckless actions; side-effect check needed |\n| 9 | **Behaviour-basis composition with black-box coefficient search.** Build a basis (persistence, verification, brevity, tool-use, format) and let TPE or CMA-ES search coefficients on dev, constrained by KL on held-out chat | Steer2Adapt (+8.2%); Heretic's TPE + KL; Evo-L2S | Basis vectors; dev split; KL reference set | High overfitting risk. Requires strict dev/test isolation |\n| 10 | **Projection ablation of a \"give-up / premature-finish\" direction** (Arditi-style orthogonalisation of writer matrices), searched Heretic-style | Arditi et al.; Heretic | Contrast of states before early-submit failures vs successful continuations | Medium. Ablation is global, so may over-suppress legitimate finishing |\n| 11 | **ExPO extrapolation of the Gemma 4 31B instruction-tuning delta** (IT + \u00ce\u00b1\u00c2\u00b7(IT\n[... 1668 characters cut ...]"},{"i":32,"kind":"assistant","long":false,"text":"The latest summaries point to wrong patches as the main remaining failure. I\u2019m checking an outcome-based edit: compare successful and failed attempts on the same tasks, then use a closed-form map to shift their writer outputs. This differs from the prior instruction-vector edits and will need a matched control and syntax checks."},{"i":33,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/replay.py; head -90 /home/keith/gemma-v2/wsp31/interp/replay_top.py; cat /home/keith/gemma-v2/wsp31/tools/wlib.py | head -80'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":34,"kind":"output","long":true,"text":" succeeded in 236ms:\n#!/usr/bin/env python\n\"\"\"replay.py [--adapter DIR] [--episodes 10] [--calls 3] [--max-pos 6000] [--max-comp 600] [--probeset FILE]\n[--out FILE.json]: exact replay of logged model calls, and the likelihood of stored trajectories, without a server\n(this lane's forward pass on GPU0: run under the gpu0 lock; about 5 s per call and arm, the base arm is cached). A\n[line removed by the dashboard scrubber]\nunedited agent then produced at temperature 0 (`comp`). The model, with the adapter if one is given, is run on\nprompt + comp (teacher forcing) and reports, for solved and failed episodes and separately for the thinking part\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nname would change. For the base arm it also prints the difference to the log-probs the rollout server logged (a\ncheck of the forward pass against the served model). Calls are spread evenly over each episode; completions longer\nthan --max-comp are cut (the kept prefix is still exact). An edit that lowers the likelihood of solved trajectories\nmuch more than that of failed ones is suspect; a higher likelihood is not evidence of more solved tasks.\"\"\"\nimport argparse\nimport hashlib\nimport json\nimport os\nimport sys\n[... 226 lines cut ...]\n    for part in s.split(\",\"):\n        if \"-\" in part:\n            a, b = part.split(\"-\")\n            out += list(range(int(a), int(b) + 1))\n        else:\n            out.append(int(part))\n    assert all(0 <= x < n for x in out)\n    return out"},{"i":35,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'Get-Content turn4/build_fidelity.py -TotalCount 200; Get-Content turn4/prepare_fidelity.py -TotalCount 140' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":36,"kind":"output","long":true,"text":" succeeded in 38ms:\n\"\"\"Closed-form rank-4 code/prose subspace edits. CPU, no optimizer.\"\"\"\nimport sys,json,argparse,hashlib\nfrom pathlib import Path\nimport torch\nA=Path('/home/keith/gemma-v2/wsp31/authors/gpt');C=A/'code/turn4';S=A/'scratch/turn4'\nsys.path.insert(0,str(C/'tools'))\nfrom edits import EditSet\ntorch.set_num_threads(8);torch.set_grad_enabled(False)\ndef unit(x):return x/x.norm(dim=-1,keepdim=True).clamp_min(1e-20)\ndef fit():\n    data=[torch.load(S/f'capture_{i}.pt',weights_only=False) for i in range(6)]\n    out={};diag={}\n    for space in ['attn_write','mlp_write','attn_read','mlp_read']:\n        p=torch.stack([x['means'][space]['code'] for x in data]).double()\n        n=torch.stack([x['means'][space]['thought'] for x in data]).double()\n        common=unit((p+n).mean(0));diff=p-n\n        diff=diff-(diff*common[None]).sum(-1,keepdim=True)*common[None]\n        vec=[];weight=[];kept=[];cos=[]\n        for l in range(60):\n[... 213 lines cut ...]\n+print('SELECTED',len(fit),len(check),json.dumps(summary,indent=1))\n+for p in (fit+check)[:2]:\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n+# Freeze only tool sources, with byte hashes, under author-owned code.\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))"},{"i":37,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/prepare.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/prepare.py' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":38,"kind":"output","long":false,"text":" succeeded in 265ms:"},{"i":39,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/prepare.py > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/prepare.log 2>&1'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":40,"kind":"output","long":true,"text":"diff --git a/turn10/inspect.py b/turn10/inspect.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..af7e4eaaf226ec36a85c1bf73e83173e545ec8f4\n--- /dev/null\n+++ b/turn10/inspect.py\n@@ -0,0 +1,26 @@\n+from pathlib import Path\n+import json,re\n+R=Path('/home/keith/gemma-v2'); A=R/'wsp31/authors/gpt'; C=A/'code/turn10'; S=A/'scratch/turn10'\n+C.mkdir(exist_ok=True); S.mkdir(exist_ok=True)\n+survey=(R/'tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md').read_text()\n+print(survey[survey.index('## C.'):survey.index('## D.')])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines()\n+for i,l in enumerate(rep):\n[line removed by the dashboard scrubber]\n+  if i<400: print('\\n'.join(rep[max(0,i-2):i+12]))\n+print('LEDGER RECIPES')\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0025','0031','0035','0038','0039','0043','0044']:\n+  txt=p.read_text(); print(p.name,txt[:10000])\n[... 70 lines cut ...]\n[line removed by the dashboard scrubber]\n+# Freeze only tool sources, with byte hashes, under author-owned code.\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n**Checking specific time reference**\n succeeded in 15036ms:"},{"i":41,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -12 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/prepare.log; cat /home/keith/gemma-v2/wsp31/tools/netops.py | head -150; cat /home/keith/gemma-v2/wsp31/tools/gpu0_session.sh | head -110'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":42,"kind":"output","long":true,"text":" succeeded in 217ms:\n                    self.filepath = file_path\n                    return True\n        return False\n<|\"|>,old_string:<|\"|>        if path in self._mtimes:\n[line removed by the dashboard scrubber]\n                if file_path not in current_files:\n                    del self._mtimes[path][file_path]\n                    self.filepath = file_path\n                    return True\n        return False\n        return False\n<|\"|>}<tool_call|><|tool_response>\n\"\"\"netops.py: network-wide operations of EditSet (edits.py), for edits of the size real training makes: many layers,\nreaders and writers, a few directions per matrix, 0.3% to 3% of the whole network. CPU only. Use through EditSet:\n\n    e = EditSet()\n    e.write_dir(range(60), D, alpha=1.0)      # every o_proj and down_proj: dW = alpha * P W   (P projects on D)\n    e.read_dir(range(60), D, alpha=1.0)       # every q/k/v/gate/up_proj:   dW = alpha * W P\n    e.scale_to(per_matrix=1.0, net_rel=0.003) # every changed matrix the same relative size, whole network 0.3%\n[... 304 lines cut ...]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n+# Freeze only tool sources, with byte hashes, under author-owned code.\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n[line removed by the dashboard scrubber]"},{"i":43,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'head -65 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/prepare.log; tail -130 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/prepare.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":44,"kind":"output","long":true,"text":" succeeded in 208ms:\n[line removed by the dashboard scrubber]\nREQUEST_SCALAR {'finish_reason': 'STOP', 'is_agent_call': True, 'policy_version': None}\nSELECTED 8 1 [\n {\n  \"instance\": \"r1chardj0n3s__parse.30da9e4f.func_basic__83wal9im\",\n  \"split\": \"fit\",\n  \"pos\": {\n   \"batch\": \"x004\",\n   \"arm\": \"base\",\n   \"call\": 2,\n   \"tool\": \"edit_file\",\n   \"start\": 4922,\n   \"request_sha256\": \"e475c67e3580dda32813bc1f8d6e613f3a3ed13a71e3fe098e9ce17a96333206\"\n  },\n  \"neg\": {\n   \"batch\": \"x004\",\n   \"arm\": \"aa\",\n   \"call\": 2,\n   \"tool\": \"edit_file\",\n[... 168 lines cut ...]\n[line removed by the dashboard scrubber]\n                if file_path not in current_files:\n                    del self._mtimes[path][file_path]\n                    self.filepath = file_path\n                    return True\n        return False\n        return False\n<|\"|>}<tool_call|><|tool_response>"},{"i":45,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"Get-Content turn10/inspection.txt | Select-String -Pattern '\"'^00|''^## Exact recipe|''^## Prediction'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":46,"kind":"output","long":true,"text":" succeeded in 69ms:\n\n0025-gpt-code-writer-damp-r4-033.md ---\n## Exact recipe\n## Prediction (written before the run)\n0031-claude-icv-brief-b20.md ---\n## Exact recipe\n0035-gpt-source-grounding-icv-b3.md ---\n## Exact recipe\n0038-claude-fcv-brief-b20.md ---\n0032's regime (+3.0, wrong patches up). That stack is not intended; on a champion that holds 0031 this entry should\n## Exact recipe\n0039-claude-fcv-brief-exact-b20.md ---\n0031 `icv-brief-b20` and 0032 `icv-brief-b40` write the mean stream shift of a \"keep your thinking very short\"\n## Exact recipe\n0043-gemini-spec-audit-thought-gate.md ---\n## Exact recipe\n0044-gemini-dual-audit-postedit-boost.md ---\n## Exact recipe\n## Prediction (written before the run)\n[... 196 lines cut ...]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n+# Freeze only tool sources, with byte hashes, under author-owned code.\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))"},{"i":47,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/prepare.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/prepare.py' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":48,"kind":"output","long":false,"text":" succeeded in 281ms:"},{"i":49,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/prepare.py > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/prepare.log 2>&1'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":50,"kind":"output","long":true,"text":"diff --git a/turn10/inspect.py b/turn10/inspect.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..af7e4eaaf226ec36a85c1bf73e83173e545ec8f4\n--- /dev/null\n+++ b/turn10/inspect.py\n@@ -0,0 +1,26 @@\n+from pathlib import Path\n+import json,re\n+R=Path('/home/keith/gemma-v2'); A=R/'wsp31/authors/gpt'; C=A/'code/turn10'; S=A/'scratch/turn10'\n+C.mkdir(exist_ok=True); S.mkdir(exist_ok=True)\n+survey=(R/'tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md').read_text()\n+print(survey[survey.index('## C.'):survey.index('## D.')])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines()\n+for i,l in enumerate(rep):\n[line removed by the dashboard scrubber]\n+  if i<400: print('\\n'.join(rep[max(0,i-2):i+12]))\n+print('LEDGER RECIPES')\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0025','0031','0035','0038','0039','0043','0044']:\n+  txt=p.read_text(); print(p.name,txt[:10000])\n[... 76 lines cut ...]\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n succeeded in 18291ms:\n**Reviewing ledger reading and normalization**\n**Applying ridge regression with low-rank SVD**"},{"i":51,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'head -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/prepare.log; cat /home/keith/gemma-v2/wsp31/tools/edits.py | head -95; grep -n -A38 replay.py /home/keith/gemma-v2/wsp31/interp/REPORT.md | head -55'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":52,"kind":"output","long":true,"text":" succeeded in 224ms:\n[line removed by the dashboard scrubber]\nREQUEST_SCALAR {'finish_reason': 'STOP', 'is_agent_call': True, 'policy_version': None}\nSELECTED 18 3 [\n {\n\"\"\"edits.py: write closed-form weight edits of Gemma 4 31B in Python and pack them as a LoRA adapter (CPU only).\n\n    from edits import EditSet\n    e = EditSet()\n    e.row_add(30, \"gate_proj\", 123, delta)        # dW[123, :] += delta      (what neuron 123 of layer 30 reads)\n    e.col_add(30, \"down_proj\", 123, delta)        # dW[:, 123] += delta      (what it writes)\n    e.neuron(30, 123, up=vec, down=vec2, mode=\"set\")   # replace the neuron's up row and down column outright\n    e.neuron_scale(30, 123, down=0.0)             # ablate the neuron (scale its write by 0)\n    e.add(41, \"o_proj\", U, V)                     # any low-rank term: dW += U @ V, U [out, k], V [k, in]\n    e.save(\"adapters/my_edit\")                    # -> adapter_model.safetensors, adapter_config.json, edit.json\n\nA module's adapter rank is (#edited rows) + (#edited columns) + (sum of k of the low-rank terms); the adapter rank\nis the largest over modules and must not exceed the server's --max-lora-rank (32 by default). Row and column edits\nare exact up to bf16 storage of the delta (8 significant bits per element): the selector factor is a one-hot.\nModules: q_proj k_proj v_proj o_proj gate_proj up_proj down_proj of layers 0..59 (shapes in ARCH.md). The ten global\n[... 455 lines cut ...]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n+# Freeze only tool sources, with byte hashes, under author-owned code.\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))"},{"i":53,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/outcome_map.py turn10/hold1.sh wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":54,"kind":"output","long":false,"text":" succeeded in 266ms:"},{"i":55,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup bash /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/hold1.sh > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":56,"kind":"output","long":true,"text":" succeeded in 229ms:\n382083\n\ndiff --git a/turn10/hold1.sh b/turn10/hold1.sh\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..c1c26191499ad267857281209e963fe377ec229d\n--- /dev/null\n+++ b/turn10/hold1.sh\n@@ -0,0 +1,11 @@\n+#!/bin/bash\n+set -euo pipefail\n+R=/home/keith/gemma-v2\n+A=$R/wsp31/authors/gpt\n+export WSP31_WORK=$A/scratch/turn10\n+export CUDA_VISIBLE_DEVICES=0\n+export OMP_NUM_THREADS=8\n+export MKL_NUM_THREADS=8\n+export PYTHONUNBUFFERED=1\n+cd \"$A\"\n+exec flock \"$R/wsp31/gpu0.lock\" timeout 1620 \"$R/tii-venv/bin/python\" \"$A/code/turn10/outcome_map.py\" hold\n[... 253 lines cut ...]\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n**Analyzing data handling and GPU constraints**\n**Evaluating completion criteria**"},{"i":57,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -8 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1_started.json; du -sh /home/keith/gemma-v2/wsp31/authors/gpt/scratch'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":58,"kind":"output","long":false,"text":" succeeded in 254ms:\n09:06:21 MODEL\n09:06:28 CAPTURE r1chardj0n3s__parse.30da9e4f.func_basic__83wal9im pos 7067 6.3\n09:06:34 CAPTURE r1chardj0n3s__parse.30da9e4f.func_basic__83wal9im neg 7068 6.13\n{\"start\": 1794665179.3569732, \"pid\": 382085, \"limit\": 1620}3.6G\t/home/keith/gemma-v2/wsp31/authors/gpt/scratch"},{"i":59,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'Get-Content turn10/inspection.txt | Select-Object -Skip 105 -First 175' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":60,"kind":"output","long":true,"text":" succeeded in 78ms:\n- attn_write: top four directions retain 91.20% of task-contrast squared energy on average over layers; mean split-half direction cosine 0.6960.\n- mlp_write: top four directions retain 88.93% of task-contrast squared energy on average over layers; mean split-half direction cosine 0.6335.\n\n[line removed by the dashboard scrubber]\n\n[line removed by the dashboard scrubber]\n\nAudit motivation: b001 has 700 edit_file calls, 541 captured status=ok responses, 49 captured status=error responses, and 110 without a captured response; 34 errors mention string matching. The first loose text scan also matched source-code strings, so only parsed tool status counts are used (code/turn4/edit_error_audit.json). Two failure examples: Mimino666__langdetect.a1598f1a.lm_rewrite__dk9wx21q (base call 19) and PyCQA__flake8.cf1542ce.lm_rewrite__yh5du3ns (base call 14): old_string not found. These observations motivate the experiment; they do not identify the cause of every wrong patch.\n\nEdit weights SHA256: cc61e0e3e4b7346c081f7bc0ae3f9d86e49d5788d919b62fee7e66b62190810c\n\nControl weights SHA256: 926273ebb4316d6a8a71b0c0e3432b02a186393146318638c5fddd1527fe9e8e\n\nRunner facts (2026-11-13 08:17:17 EST): source `wsp31/authors/gpt/queue/code-writer-damp-r4-033/`; served copy `wsp31/queue/frozen/[task]/`; sha256 over files, edit `7af6609c85c90616da21231a223e534ab8b0933ba9c492ee1126b9b0e69e6a95`, control `21d25e1a07a9adb9c238e67293939e7e241ed31d4960074798b336433bc7778c`; both passed the checker.\n\n## Prediction (written before the run)\n\npredicted_gain_120: -6 to 12\n\n[... 427 lines cut ...]\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n**Analyzing tensor output reliability**\n**Reviewing multi-stage evaluation process**"},{"i":61,"kind":"tool","long":false,"text":"[line removed by the dashboard scrubber]"},{"i":62,"kind":"output","long":true,"text":" succeeded in 242ms:\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n592:correlational, three runs per task, greedy decoding with serving noise); why finished patches are wrong (the\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n907:`dirs/out/replay_agree.json`; `cd wsp31/interp/dirs && python replay_agree.py --out out/replay_agree.json`. Top\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n983:Limits: correlational; three greedy runs per task under serving noise; snapshot of a batch that was still\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n1922:  `dirs.py`, `post.py`, `dose.py`, `dose2.py`, `dose_eval.py`, `replay_agree.py`, `render_check.py`, `synth.py`;\n[... 18 lines cut ...]\n09:06:46 CAPTURE [task] neg 6982 6.12\n09:06:54 CAPTURE [task] pos 9585 8.31\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."},{"i":63,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'Get-Content turn10/inspection.txt | Select-Object -Skip 280 -First 110' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":64,"kind":"output","long":true,"text":" succeeded in 77ms:\nPositive paragraph (I1):\n> Important: ground every change in current source text and observed tool results. Read the relevant implementation before editing. Copy old_string exactly from the latest file contents. After a tool error, use its message to correct the next action instead of repeating the failed call. Check the resulting diff against the requested behavior before submitting.\n\nGeneric paragraph (I0):\n> Important: work on the user's coding task with the tools provided in this session. The repository contains source files and supporting files. Tool calls take arguments and return results. Follow the task description while deciding what action to take next. Continue working on the task using the available context and provide your final response when finished.\n\n[line removed by the dashboard scrubber]\n\nFor each layer L, d_L is the task-weighted mean of resid_post(I1) minus resid_post(I0) at matched continuation positions. Set delta_L = d_L - layer_scalar_L * d_(L-1), with d_(-1)=0. Split-half direction cosine, min/median/max over layers: -0.001, 0.478, 0.914.\n\nChoose the neuron with the third-smallest mean absolute activation in each layer on these captures. Fit w so w dot mlp_in is about 1: compare the mean-input read with a dual ridge solve (regularizer N times the mean squared input coordinate); use ridge only if its standard deviation on calibration calls is below 0.7 of the mean read's and its calibration mean is between 0.9 and 1.1. Calibration calls have capture index modulo 3 equal to zero; the others fit w. If the absolute BOS score exceeds 3, remove that BOS direction and rescale. Set the gate row to 8w and the up row to w. The new activation is approximately 8(w dot x)^2, not a true constant. Its calibration coefficient of variation has min/median/max 0.057, 0.116, 0.582.\n\nThe new down column is clipdiv(beta * delta_L, post_feedforward_norm_weight) times mean_raw_MLP_RMS / (mean_new_activation * layer_scalar_L). clipdiv zeroes the lowest 5% of absolute post-norm weights before inversion. Save row/column differences against the unedited weights. This is a first-order write approximation: it ignores the new column's change to RMS and the response of later layers. It also averages away the position-dependent part of the instruction and does not reproduce its attention patterns. It acts at prompt positions too. Bf16 factors add rounding.\n\nControl: identical gate/up changes, neuron, layers, rank and dose. First flip the signs of the intended NEW down column c with seed 710000 + L. Let u be the unit old column, a = (c dot u)u, and z be the randomized column projected off u. Set the new control column to a + z * norm(c-a)/norm(z), then subtract the old column to form the update. This preserves the norm of the new write and its projection onto the old column, so the total column-update norm also matches before rounding. The remaining direction is random. The largest stored per-matrix norm mismatch is 0.00066. Stored new-column raw-norm ratio (control/edit), min/median/max: [0.998871023544941, 0.9999547802018586, 1.0015328220316937]. The corresponding post-norm-weighted ratio: [0.99786242540014, 0.9999814337979892, 1.0303488934770586]. This controls update direction while holding the read edits fixed. An initial whole-update sign control was discarded before edited replay because it could leave a large old-column write under the new gate; CONTROL_AMENDMENT.md records the correction. Those discarded controls are not this entry's ctrl/.\n\nRebuild: bash build.sh OUT_DIR invokes code/turn7/build_ground.py from frozen code/turn7/ground_stats.pt. ground_cpu.py captured and solved the statistics on CPU with 16 threads and dense-weight caching. ground_job.py supplies the compiler used for rebuilds. Both use a frozen copy of the documented tools in code/turn7/tools. The compiler adapts claude's turn-6 icv_job.py; ground_job.py and the small thinklib.py contain the complete changed code path. No optimizer, grad\n[... 1091 characters cut ...]"},{"i":65,"kind":"assistant","long":true,"text":"I found 18 tasks with both successful and failed reference attempts, plus three separate tasks for checks. The fit uses editing decisions matched by task and tool, and adds constraints to preserve successful states, prompts, and tool syntax. GPU 0 is now capturing those states under the shared lock.\n\napply patch\npatch: completed\nC:\\Users\\Owner\\wsp31_loop\\work\\gpt\\turn10\\audit.py\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/hold1.sh b/turn10/hold1.sh\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..c1c26191499ad267857281209e963fe377ec229d\n--- /dev/null\n+++ b/turn10/hold1.sh\n@@ -0,0 +1,11 @@\n+#!/bin/bash\n+set -euo pipefail\n+R=/home/keith/gemma-v2\n+A=$R/wsp31/authors/gpt\n+export WSP31_WORK=$A/scratch/turn10\n+export CUDA_VISIBLE_DEVICES=0\n+export OMP_NUM_THREADS=8\n+export MKL_NUM_THREADS=8\n+export PYTHONUNBUFFERED=1\n+cd \"$A\"\n+exec flock \"$R/wsp31/gpu0.lock\" timeout 1620 \"$R/tii-venv/bin/python\" \"$A/code/turn10/outcome_map.py\" hold\ndiff --git a/turn10/inspect.py b/turn10/inspect.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..af7e4eaaf226ec36a85c1bf73e83173e545ec8f4\n--- /dev/null\n+++ b/turn10/inspect.py\n@@ -0,0 +1,26 @@\n+from pathlib import Path\n+import json,re\n+R=Path('/home/keith/gemma-v2'); A=R/'wsp31/authors/gpt'; C=A/'code/turn10'; S=A/'scratch/turn10'\n+C.mkdir(exist_ok=True); S.mkdir(exist_ok=True)\n+survey=(R/'tii-wsp31-doc/reports/2026-11-12-weight-editing-survey.md').read_text()\n+print(survey[survey.index('## C.'):survey.index('## D.')])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines()\n+for i,l in enumerate(rep):\n[line removed by the da\n[... 13868 characters cut ...]"},{"i":66,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/audit.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":67,"kind":"output","long":false,"text":" succeeded in 274ms:"},{"i":68,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/audit.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":69,"kind":"output","long":true,"text":" succeeded in 332ms:\nBOUNDARY PASS 21 tasks 42 episodes 9 stage2 exclusion lists\n\nLEDGER 0007-claude-deep-gate-b01-end-neurons-x9.md \n ## Hypothesis\n\nIn the unedited batch b001 (three identical arms, 61 episodes finished when read) 14 of the 28 failures end at the\n7.5-minute session limit, at least 10 of them with an empty patch and 8 of those without a single file edit (at 110\nepisodes, 9:40 PM ET: solved 44%, at the limit 35%, empty patch 25%). At about\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n\"Wait, ...\" restarts. Making long thoughts end sooner should return that wall-clock to tool calls, so that episodes\nwhich now time out without a patch get to edit, test and submit.\n\nDifferent from the E4B \"think briefly\" edits (28 / 28 / 25 vs 29, PRIOR_E4B.md): there the session limit was not\nreported as binding; here it ends 23% to 35% of unedited episodes, and the edit is built from the state at the logged ends of\nthoughts (and, in families B and C, acts only deep inside a long thought), not from a short-vs-long contrast.\n\n\n[... 654 lines cut ...]\n+dst=C/'tools';dst.mkdir(exist_ok=True)\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n**Reviewing memory and code inspection details**\n**Analyzing build process and artifact consistency**"},{"i":70,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'grep -A12 -n def.base_weight /home/keith/gemma-v2/wsp31/tools/g31.py; tail -8 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; cat /home/keith/gemma-v2/wsp31/tools/rescale.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":71,"kind":"output","long":true,"text":" succeeded in 233ms:\n162:    def base_weight(self, l, mod):\n163-        \"\"\"Dequantised checkpoint weight, bf16 [out, in] (k_proj for v_proj on global layers).\"\"\"\n164-        if mod == \"v_proj\" and not self.arch.geom(l)[\"has_v\"]:\n165-            mod = \"k_proj\"\n166-        if (l, mod) in self._dense:\n167-            return self._dense[(l, mod)]\n168-        w = dequant(*self.L[l][mod])\n169-        if self.cache_dense:\n170-            self._dense[(l, mod)] = w\n171-        return w\n172-\n173-    def weight(self, l, mod):\n174-        \"\"\"Weight the forward pass uses for the base path: an override if one is set, else the checkpoint.\"\"\"\n09:08:19 CAPTURE pallets__jinja.ada0a9a6.func_basic__2vdao9be neg 9130 7.94\n09:08:29 CAPTURE r1chardj0n3s__parse.30da9e4f.func_pm_remove_cond__k4df18dk pos 11576 10.02\n09:08:36 CAPTURE r1chardj0n3s__parse.30da9e4f.func_pm_remove_cond__k4df18dk neg 8166 7.09\n09:08:45 CAPTURE [task] pos 10582 9.19\n09:08:54 CAPTURE [task] neg 10555 9.17\n09:09:00 CAPTURE [task] pos 6763 5.89\n[... 378 lines cut ...]\n+for f in T.glob('*.py'):shutil.copy2(f,dst/f.name)\n+(dst/'data').mkdir(exist_ok=True)\n+shutil.copy2(T/'data/fro_norms.json',dst/'data/fro_norms.json')\n+(C/'tools_sha256.json').write_text(json.dumps({f.name:hashlib.sha256(f.read_bytes()).hexdigest() for f in dst.glob('*.py')},indent=2))\n\n**Estimating processing and throughput times**\n**Reviewing testing parameters and performance**\n**Estimating resource feasibility**"},{"i":72,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/dose.py | head -135; cat /home/keith/gemma-v2/wsp31/interp/toolcall_check.py | head -165; tail -7 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":73,"kind":"output","long":true,"text":" succeeded in 245ms:\n#!/usr/bin/env python\n[line removed by the dashboard scrubber]\n[--tol 0.10] [--save-largest DIR] [--champion current|DIR] [--out FILE.json] | dose.py --selftest: how large can this edit be made before the\nagent stops producing well-formed turns? Run inside a gpu0 session (a running server with runtime adapter loading).\nFor each dose (whole-network size, 0.003 = 0.3%) the tool writes a copy of the edit scaled by one common factor\n(rescale.py: every matrix keeps its share), loads it under a content-hash name, measures, unloads and deletes the\ncopy. Measured per dose, always next to the unedited model on the same prompts: (1) at labelled decision points of\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nwell-formed tool call (<|tool_call>call:NAME{...}<tool_call|> with a tool name the harness has, outside thinking),\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nis coherent when its share of well-formed tool calls is within --tol of the unedited model's and its shares of\nmalformed, never-closed, empty and repetitive turns are no more than --tol above it. The last line names the largest\ncoherent dose (all smaller doses coherent too). This says the model still works as an agent at that size; it says\nnothing about whether the edit helps. --mode alpha scales through lora_alpha instead of rewriting the file (dose\ntests only: such a directory is not a valid queue entry). With --champion (or WSP31_CHAMPION) the reference is the\nchampion and every dose is served as champion + scaled edit; doses are still sizes of your edit alone. --selftest classifies the logged answers (CPU).\"\"\"\n[... 1015 lines cut ...]\n+   rr=[r for r in rows if r['at']==at]\n[line removed by the dashboard scrubber]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()"},{"i":74,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/served.py turn10/rebuild.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":75,"kind":"output","long":false,"text":" succeeded in 267ms:"},{"i":76,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/served.py --panel-only; tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":77,"kind":"output","long":true,"text":" succeeded in 1914ms:\nPANEL 112 52\n09:10:39 CAPTURE [task] neg 7545 6.5\n09:10:49 CAPTURE [task] pos 10426 9.05\n09:10:59 CAPTURE [task] neg 11173 9.7\n09:11:06 CAPTURE mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm pos 8771 7.65\n09:11:15 CAPTURE mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm neg 9411 8.13\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n[... 830 lines cut ...]\n+   rr=[r for r in rows if r['at']==at]\n[line removed by the dashboard scrubber]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()"},{"i":78,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/served.py turn10/inspect_progress.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":79,"kind":"output","long":false,"text":" succeeded in 300ms:"},{"i":80,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -9 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/inspect_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":81,"kind":"output","long":true,"text":" succeeded in 1029ms:\n09:10:33 CAPTURE [task] pos 9065 7.84\n09:10:39 CAPTURE [task] neg 7545 6.5\n09:10:49 CAPTURE [task] pos 10426 9.05\n09:10:59 CAPTURE [task] neg 11173 9.7\n09:11:06 CAPTURE mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm pos 8771 7.65\n09:11:15 CAPTURE mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm neg 9411 8.13\n09:11:21 CAPTURE lepture__mistune.bf54ef67.combine_module__dalnbilu pos 7198 6.25\n09:11:28 CAPTURE lepture__mistune.bf54ef67.combine_module__dalnbilu neg 7651 6.62\n09:11:34 CAPTURE prettytable__prettytable.ca90b055.combine_file__2mwa4qpg pos 6917 6.07\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n[... 421 lines cut ...]\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Processing attention weights and outcome labels**\n**Evaluating computation strategies on CPU and GPU**\n**Managing race conditions**"},{"i":82,"kind":"assistant","long":false,"text":"The capture is nearly complete. The main caveat is that episode success does not prove each edit was correct. I\u2019ll check whether the fitted map transfers to the three reserved tasks, then test the dose range for changed decisions, preserved thought endings, and valid tool calls."},{"i":83,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -6 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/inspect_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":84,"kind":"output","long":true,"text":" succeeded in 959ms:\n09:11:40 CAPTURE prettytable__prettytable.ca90b055.combine_file__2mwa4qpg neg 6692 5.93\n09:11:40 FIT 18 3 mean check cosine 0.07760504063112345 retained 0.5427474183864531\n09:11:41 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E033 0.003300000090131365 120\n09:11:41 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E100 0.009999999793127694 120\n09:11:42 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E300 0.03000000082936939 120\n09:11:43 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/C100 0.009999999793127694 120\nDIAGNOSTICS o_proj\n0 20 {'retained': 0.6057944316894114, 'fit_error': 0.6923969871067123, 'check_error': 1.0078041087721195} cos 0.06856088848230853\n20 40 {'retained': 0.5355620455581478, 'fit_error': 0.6936781239290354, 'check_error': 1.0057906440552125} cos 0.1018633714965034\n40 60 {'retained': 0.5716482943441719, 'fit_error': 0.715048528518079, 'check_error': 1.0051635305975537} cos 0.07635008654283564\nDIAGNOSTICS down_proj\n0 20 {'retained': 0.5052666207433784, 'fit_error': 0.7725324637919686, 'check_error': 1.0034682774506956} cos 0.05213358997401563\n20 40 {'retained': 0.49642569434498973, 'fit_error': 0.7298701313842395, 'check_error': 0.998999522814173} cos 0.09174956637672978\n40 60 {'retained': 0.54178742363862, 'fit_error': 0.7236737932622003, 'check_error': 1.0041875509296694} cos 0.07497274091434769\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n[... 425 lines cut ...]\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Analyzing high-dimensional mapping challenges**\n**Evaluating test reliability and metric sensitivity**"},{"i":85,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/inspect_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":86,"kind":"output","long":true,"text":" succeeded in 940ms:\n09:11:41 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E033 0.003300000090131365 120\n09:11:41 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E100 0.009999999793127694 120\n09:11:42 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E300 0.03000000082936939 120\n09:11:43 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/C100 0.009999999793127694 120\n09:12:22 EVAL 0 mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm 67 ['base', 'E033', 'E100', 'E300', 'C100']\nDIAGNOSTICS o_proj\n0 20 {'retained': 0.6057944316894114, 'fit_error': 0.6923969871067123, 'check_error': 1.0078041087721195} cos 0.06856088848230853\n20 40 {'retained': 0.5355620455581478, 'fit_error': 0.6936781239290354, 'check_error': 1.0057906440552125} cos 0.1018633714965034\n40 60 {'retained': 0.5716482943441719, 'fit_error': 0.715048528518079, 'check_error': 1.0051635305975537} cos 0.07635008654283564\nDIAGNOSTICS down_proj\n0 20 {'retained': 0.5052666207433784, 'fit_error': 0.7725324637919686, 'check_error': 1.0034682774506956} cos 0.05213358997401563\n20 40 {'retained': 0.49642569434498973, 'fit_error': 0.7298701313842395, 'check_error': 0.998999522814173} cos 0.09174956637672978\n40 60 {'retained': 0.54178742363862, 'fit_error': 0.7236737932622003, 'check_error': 1.0041875509296694} cos 0.07497274091434769\nEVAL records 1\nmozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm [('E033', 0, -0.00033891317434608936), ('E100', 2, -0.01906244270503521), ('E300', 2, -0.11239234358072281), ('C100', 1, -0.02401219680905342)]\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n[... 425 lines cut ...]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Optimizing learning and computation**"},{"i":87,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/rebuild.py /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100 --dose 0.01 > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":88,"kind":"output","long":false,"text":" succeeded in 201ms:\n399087"},{"i":89,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/tools/fastprobe.py | head -200; cat /home/keith/gemma-v2/wsp31/tools/check_adapter.py | tail -40'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":90,"kind":"output","long":true,"text":" succeeded in 228ms:\n#!/usr/bin/env python\n\"\"\"fastprobe.py EDIT_DIR --port PORT [--traces 12] [--per-trace 8] [--max-pos 8000] [--keep] [--champion current|DIR] [--out FILE.json]:\nfast behavioural probe of an edit on a running vLLM server (no rollouts; the server must have been started with\nruntime adapter loading, as gpu0_session.sh does). It loads the adapter under a name derived from the hash of its\n[line removed by the dashboard scrubber]\nlabelled decision points of stored agent traces for the base model and for the edit, unloads the adapter, and\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n(think), <|tool_call> and <turn|>. Base answers are cached per server start in data/cache. Because only the top 20\n[line removed by the dashboard scrubber]\nthe same measurement over the full vocabulary without a server. With --champion (or WSP31_CHAMPION) the reference\narm is the champion adapter and the edit is served stacked on it (champ.py), as the runner serves an entry.\n\"\"\"\nimport argparse\nimport hashlib\nimport json\nimport os\nimport sys\nimport time\n[... 1003 lines cut ...]\n+   rr=[r for r in rows if r['at']==at]\n[line removed by the dashboard scrubber]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()"},{"i":91,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/inspect_progress.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":92,"kind":"output","long":false,"text":" succeeded in 282ms:"},{"i":93,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; tail -3 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/inspect_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":94,"kind":"output","long":true,"text":" succeeded in 1225ms:\n09:11:41 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E100 0.009999999793127694 120\n09:11:42 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/E300 0.03000000082936939 120\n09:11:43 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/scouts/C100 0.009999999793127694 120\n09:12:22 EVAL 0 mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm 67 ['base', 'E033', 'E100', 'E300', 'C100']\n09:13:02 EVAL 1 mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm 92 ['base', 'E033', 'E100', 'E300', 'C100']\n09:13:22 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100/edit 0.0099999997806608 120\nDIAGNOSTICS o_proj\n0 20 {'retained': 0.6057944316894114, 'fit_error': 0.6923969871067123, 'check_error': 1.0078041087721195} cos 0.06856088848230853\n20 40 {'retained': 0.5355620455581478, 'fit_error': 0.6936781239290354, 'check_error': 1.0057906440552125} cos 0.1018633714965034\n40 60 {'retained': 0.5716482943441719, 'fit_error': 0.715048528518079, 'check_error': 1.0051635305975537} cos 0.07635008654283564\nDIAGNOSTICS down_proj\n0 20 {'retained': 0.5052666207433784, 'fit_error': 0.7725324637919686, 'check_error': 1.0034682774506956} cos 0.05213358997401563\n20 40 {'retained': 0.49642569434498973, 'fit_error': 0.7298701313842395, 'check_error': 0.998999522814173} cos 0.09174956637672978\n40 60 {'retained': 0.54178742363862, 'fit_error': 0.7236737932622003, 'check_error': 1.0041875509296694} cos 0.07497274091434769\nEVAL records 2\nmozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm [('E033', 0, -0.00033891317434608936), ('E100', 2, -0.01906244270503521), ('E300', 2, -0.11239234358072281), ('C100', 1, -0.02401219680905342)]\nclose [('base', [101], 0.0), ('E033', [101], 0.1054084300994873), ('E100', [101], 0.38440945744514465), ('E300', [101], 0.48356178402900696), ('C100', [109], -1.593332290649414)]\nmozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm [('E033', 1, 0.00035774181014858186), ('E100', 1, 0.002461430849507451), ('E300', 2, -0.03195725008845329), ('C100', 1, -0.0042394534684717655)]\nclose [('base', [101], 0.0), ('E033', [101], -3.6954406823497266e-06), ('E100', [101], -2.658302582858596e-05), ('E300', [101], -0.0004880375927314162), ('C100', [101], 4.649122274713591e-06)]\n[... 432 lines cut ...]\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Analyzing control states and prediction margins**\n**Evaluating dose selection and control strategies**\n**Estimating computational resource needs**"},{"i":95,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/rebuild.py /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu300 --dose 0.03 > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu300.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":96,"kind":"output","long":false,"text":" succeeded in 217ms:\n401306"},{"i":97,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/rebuild.py /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu033 --dose 0.0033 > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu033.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":98,"kind":"output","long":true,"text":" succeeded in 224ms:\n401410\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n[... 413 lines cut ...]\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Reviewing model training and validation details**\n**Verifying matrix factorization stability**"},{"i":99,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'grep -n -A16 def.scale /home/keith/gemma-v2/wsp31/tools/netops.py; grep -n -A55 def.save /home/keith/gemma-v2/wsp31/tools/edits.py; tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; tail -2 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":100,"kind":"output","long":true,"text":" succeeded in 221ms:\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n160-        c = float(c)\n161-        for store in (self.rows, self.cols):\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n164-                    for j in d:\n165-                        d[j] = d[j] * c\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n169-\n170:    def scale_to(self, net_rel=None, per_matrix=None):\n171-        \"\"\"per_matrix=x: rescale every changed matrix to |dW|_F / |W|_F = x (training moves every matrix by nearly\n172-        the same relative amount). net_rel=y: then one common factor so the whole-network size is y. With both, the\n173-        matrices are equalised first and the common factor follows (x is then only a ratio). Returns net_rel.\"\"\"\n174-        if per_matrix is not None:\n175-            for k, s in self.sizes().items():\n176-                assert s[\"fro\"] > 0, f\"{k} has a zero edit\"\n[... 479 lines cut ...]\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Verifying computation consistency**\n**Reviewing build script execution**\n**Managing complex timeout budget**"},{"i":101,"kind":"assistant","long":true,"text":"[line removed by the dashboard scrubber]\n\napply patch\npatch: completed\nC:\\Users\\Owner\\wsp31_loop\\work\\gpt\\turn10\\hold2.py\nC:\\Users\\Owner\\wsp31_loop\\work\\gpt\\turn10\\hold2.sh\nC:\\Users\\Owner\\wsp31_loop\\work\\gpt\\turn10\\prepare_checks.py\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/hold1.sh b/turn10/hold1.sh\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..c1c26191499ad267857281209e963fe377ec229d\n--- /dev/null\n+++ b/turn10/hold1.sh\n@@ -0,0 +1,11 @@\n+#!/bin/bash\n+set -euo pipefail\n+R=/home/keith/gemma-v2\n+A=$R/wsp31/authors/gpt\n+export WSP31_WORK=$A/scratch/turn10\n+export CUDA_VISIBLE_DEVICES=0\n+export OMP_NUM_THREADS=8\n+export MKL_NUM_THREADS=8\n+export PYTHONUNBUFFERED=1\n+cd \"$A\"\n+exec flock \"$R/wsp31/gpu0.lock\" timeout 1620 \"$R/tii-venv/bin/python\" \"$A/code/turn10/outcome_map.py\" hold\ndiff --git a/turn10/hold2.py b/turn10/hold2.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..e72712dfcdc3d1951af0ccbea30c730420816ad3\n--- /dev/null\n+++ b/turn10/hold2.py\n@@ -0,0 +1,17 @@\n+import time,json,os,subprocess,sys\n+from pathlib import Path\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10';T=R/'wsp31/tools';PY=R/'tii-venv/bin/python'\n+start=time.time();budget=int(sys.argv[1]);(S/'hold2_started.json').write_text(json.dumps({'start':start,'limit':budget,'pid':os.getpid()}))\n+paths=[S/'cpu100/edit',S/'cpu300/edit',S/'cpu033/edit',S/'cpu100/ctrl',S/'cpu300/ctrl',S/'cpu033/ctrl']\n+for p in paths:\n+ name=p.parent.name+'_'+p.name\n+ cmd=[str(PY),str(T/'replay.py'),'--adapter',str(p),'--probeset',str(C/'replay_panel.jsonl'),'--epi\n[... 24521 characters cut ...]"},{"i":102,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/prepare_checks.py turn10/hold2.py turn10/hold2.sh wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":103,"kind":"output","long":false,"text":" succeeded in 376ms:"},{"i":104,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -2 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu033.log; tail -2 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu300.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/prepare_checks.py > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/checks.log 2>&1'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":105,"kind":"output","long":true,"text":" succeeded in 9249ms:\n09:14:52 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu033/edit 0.0033000000860908046 120\n09:15:20 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu033/ctrl 0.0033000000860908046 120\n09:14:52 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu300/edit 0.03000000079058293 120\n09:15:19 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu300/ctrl 0.03000000079058293 120\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n[... 497 lines cut ...]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Analyzing budget constraints and timing**"},{"i":106,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; tail -8 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/checks.log; du -sh /home/keith/gemma-v2/wsp31/authors/gpt/scratch'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":107,"kind":"output","long":true,"text":" succeeded in 231ms:\n09:14:37 EVAL 4 prettytable__prettytable.ca90b055.combine_file__2mwa4qpg 60 ['base', 'E033', 'E100', 'E300', 'C100']\n09:15:07 EVAL 5 prettytable__prettytable.ca90b055.combine_file__2mwa4qpg 50 ['base', 'E033', 'E100', 'E300', 'C100']\n09:15:31 EVAL 6 [task] 41 ['base', 'E033', 'E100', 'E300', 'C100']\n09:15:49 EVAL 7 [task] 36 ['base', 'E033', 'E100', 'E300', 'C100']\n09:16:12 EVAL 8 [task] 42 ['base', 'E033', 'E100', 'E300', 'C100']\nedit {\"r\": 4, \"scale\": 2.0, \"changed\": 120, \"of\": 420, \"net_rel\": 0.03, \"rel_median\": 0.07682, \"rel_min\": 0.0768, \"rel_max\": 0.07687, \"rel_max_mod\": \"38.down_proj\", \"total_rel\": 0.07682, \"total_fro\": 61.87, \"stable_rank_median\": 2.22, \"part_rank_median\": 3.783}\n  by type {'down_proj': 0.07682, 'o_proj': 0.07682}\n  by depth (10-layer bands) [0.07682, 0.07682, 0.07682, 0.07682, 0.07682, 0.07683]\nctrl {\"r\": 4, \"scale\": 2.0, \"changed\": 120, \"of\": 420, \"net_rel\": 0.03, \"rel_median\": 0.07682, \"rel_min\": 0.0768, \"rel_max\": 0.07687, \"rel_max_mod\": \"38.down_proj\", \"total_rel\": 0.07682, \"total_fro\": 61.87, \"stable_rank_median\": 2.22, \"part_rank_median\": 3.783}\n  by type {'down_proj': 0.07682, 'o_proj': 0.07682}\n  by depth (10-layer bands) [0.07682, 0.07682, 0.07682, 0.07682, 0.07682, 0.07683]\n\nGEOMETRY {\"033\": {\"control_exact_B_sign_reverse\": true, \"cpu_vs_gpu_scout_different_stored_elements\": 2289, \"total_stored_elements\": 10035200, \"edit_sha256\": \"5f1bb2d83aad63ce853009ce0f0841871b065edbad8e6b1bf02de1d5ff785579\"}, \"100\": {\"control_exact_B_sign_reverse\": true, \"cpu_vs_gpu_scout_different_stored_elements\": 2290, \"total_stored_elements\": 10035200, \"edit_sha256\": \"aae8b4fc48aa0aebbba7cab48fa95b8835e78a09e330df4a7b6452bb67a1d6a8\"}, \"300\": {\"control_exact_B_sign_reverse\": true, \"cpu_vs_gpu_scout_different_stored_elements\": 2289, \"total_stored_elements\": 10035200, \"edit_sha256\": \"6e1f4148d4ef77b31e16757aaa4c37dc2638902c4e1bc26d4172b086c4835bf2\"}}\n4.1G\t/home/keith/gemma-v2/wsp31/authors/gpt/scratch\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n[... 507 lines cut ...]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Assessing scientific error and code diagnostics**"},{"i":108,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/inspect_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":109,"kind":"output","long":true,"text":" succeeded in 1031ms:\nDIAGNOSTICS o_proj\n0 20 {'retained': 0.6057944316894114, 'fit_error': 0.6923969871067123, 'check_error': 1.0078041087721195} cos 0.06856088848230853\n20 40 {'retained': 0.5355620455581478, 'fit_error': 0.6936781239290354, 'check_error': 1.0057906440552125} cos 0.1018633714965034\n40 60 {'retained': 0.5716482943441719, 'fit_error': 0.715048528518079, 'check_error': 1.0051635305975537} cos 0.07635008654283564\nDIAGNOSTICS down_proj\n0 20 {'retained': 0.5052666207433784, 'fit_error': 0.7725324637919686, 'check_error': 1.0034682774506956} cos 0.05213358997401563\n20 40 {'retained': 0.49642569434498973, 'fit_error': 0.7298701313842395, 'check_error': 0.998999522814173} cos 0.09174956637672978\n40 60 {'retained': 0.54178742363862, 'fit_error': 0.7236737932622003, 'check_error': 1.0041875509296694} cos 0.07497274091434769\nEVAL records 10\nmozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm [('E033', 0, -0.00033891317434608936), ('E100', 2, -0.01906244270503521), ('E300', 2, -0.11239234358072281), ('C100', 1, -0.02401219680905342)]\nclose [('base', [101], 0.0), ('E033', [101], 0.1054084300994873), ('E100', [101], 0.38440945744514465), ('E300', [101], 0.48356178402900696), ('C100', [109], -1.593332290649414)]\nmozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm [('E033', 1, 0.00035774181014858186), ('E100', 1, 0.002461430849507451), ('E300', 2, -0.03195725008845329), ('C100', 1, -0.0042394534684717655)]\nclose [('base', [101], 0.0), ('E033', [101], -3.6954406823497266e-06), ('E100', [101], -2.658302582858596e-05), ('E300', [101], -0.0004880375927314162), ('C100', [101], 4.649122274713591e-06)]\nlepture__mistune.bf54ef67.combine_module__dalnbilu [('E033', 0, 0.0015495496336370707), ('E100', 1, 0.003362029790878296), ('E300', 1, -0.02503914013504982), ('C100', 2, -0.021451076492667198)]\nclose [('base', [101], 0.0), ('E033', [101], -0.0002344941021874547), ('E100', [101], -0.004803928080946207), ('E300', [101], -0.03728201612830162), ('C100', [101], -0.00022497738245874643)]\nlepture__mistune.bf54ef67.combine_module__dalnbilu [('E033', 0, -0.003126013558357954), ('E100', 1, -0.008546711876988411), ('E300', 1, -0.03113718517124653), ('C100', 0, -0.004122549202293158)]\nclose [('base', [101], 0.0), ('E033', [101], -0.35080480575561523), ('E100', [7280], -0.8132667541503906), ('E300', [7280], -2.0825448036193848), ('C100', [101], 0.014455974102020264)]\nprettytable__prettytable.ca90b055.combine_file__2mwa4qpg [('E033', 3, -0.0032761506736278534), ('E100', 3, -0.007753655314445496), ('E300', 6, -0.14585791528224945), ('C100', 5, -0.1131465882062912)]\nclose [('base', [101], 0.0), ('E033', [101], -0.0015242259250953794), ('E100', [101], -0.005253578536212444), ('E300', [101], -0.25553980469703674), ('C100', [101], 0.0010672344360500574)]\n[... 1046 lines cut ...]\n+   rr=[r for r in rows if r['at']==at]\n[line removed by the dashboard scrubber]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()"},{"i":110,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/hold2.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":111,"kind":"output","long":false,"text":" succeeded in 339ms:"},{"i":112,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1_finished.json'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":113,"kind":"output","long":true,"text":" exited 1 in 235ms:\n09:16:12 EVAL 8 [task] 42 ['base', 'E033', 'E100', 'E300', 'C100']\n09:16:33 EVAL 9 prettytable__prettytable.ca90b055.func_basic__1mmuxqev 67 ['base', 'E033', 'E100', 'E300', 'C100']\n09:16:56 EVAL 10 [task] 44 ['base', 'E033', 'E100', 'E300', 'C100']\n09:17:15 EVAL 11 [task] 32 ['base', 'E033', 'E100', 'E300', 'C100']\n09:17:33 EVAL 12 Mimino666__langdetect.a1598f1a.lm_rewrite__dk9wx21q 38 ['base', 'E033', 'E100', 'E300', 'C100']\ncat: /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1_finished.json: No such file or directory\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n[... 501 lines cut ...]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Noting time update**"},{"i":114,"kind":"assistant","long":false,"text":"[line removed by the dashboard scrubber]"},{"i":115,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -2 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1_finished.json'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":116,"kind":"output","long":true,"text":" exited 1 in 225ms:\n09:17:15 EVAL 11 [task] 32 ['base', 'E033', 'E100', 'E300', 'C100']\n09:17:33 EVAL 12 Mimino666__langdetect.a1598f1a.lm_rewrite__dk9wx21q 38 ['base', 'E033', 'E100', 'E300', 'C100']\ncat: /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1_finished.json: No such file or directory\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n[... 500 lines cut ...]\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':rows,'summary':summary})\n+  (S/'generation.json').write_text(json.dumps(out));print('ARM',name,json.dumps(summary),'seconds',round(prev,1),flush=True)\n+ print('DONE',round(time.time()-start,1),flush=True)\n+if __name__=='__main__':main()\n\n**Managing model and data captures**\n**Optimizing audit and cleanup**\n**Managing cache files safely**"},{"i":117,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1_finished.json; tail -1 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold1.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":118,"kind":"output","long":true,"text":" succeeded in 203ms:\n{\"start\": 1794665179.3569732, \"end\": 1794665877.3871129, \"seconds\": 698.0301401615143}09:17:57 SUMMARY {\"C100\": {\"all\": {\"n\": 772, \"flips\": 18, \"dlogp\": -0.028410632298400365, \"kl\": 0.017361596188088156, \"top101\": 12, \"dclose\": -2.16575953132748}, \"thought\": {\"n\": 403, \"flips\": 15, \"dlogp\": -0.03459661653630491, \"kl\": 0.02311431030481684, \"top101\": 0, \"dclose\": -1.2701146691372023}, \"close\": {\"n\": 14, \"flips\": 2, \"dlogp\": -0.27832514952595894, \"kl\": 0.11389414092627703, \"top101\": 12, \"dclose\": -0.27832514952595894}, \"action\": {\"n\": 305, \"flips\": 1, \"dlogp\": -0.01196418921087764, \"kl\": 0.007688858980733041, \"top101\": 0, \"dclose\": -3.5120652058085455}, \"delimiter\": {\"n\": 50, \"flips\": 0, \"dlogp\": -0.00889883019041008, \"kl\": 0.0029693087957275567, \"top101\": 0, \"dclose\": -1.7006758499145507}, \"records\": 14}, \"E033\": {\"all\": {\"n\": 772, \"flips\": 10, \"dlogp\": 0.00022059869880117284, \"kl\": 0.0015974341749353577, \"top101\": 14, \"dclose\": 1.4345653304164274}, \"thought\": {\"n\": 403, \"flips\": 10, \"dlogp\": 0.0005749486636361177, \"kl\": 0.0025078605481471967, \"top101\": 0, \"dclose\": 0.9670938558081539}, \"close\": {\"n\": 14, \"flips\": 0, \"dlogp\": -0.0030747721606790685, \"kl\": 0.007384444726714686, \"top101\": 14, \"dclose\": -0.0030747721606790685}, \"action\": {\"n\": 305, \"flips\": 0, \"dlogp\": -0.00028492837426129567, \"kl\": 0.00036514690315224933, \"top101\": 0, \"dclose\": 2.2102262778360338}, \"delimiter\": {\"n\": 50, \"flips\": 0, \"dlogp\": 0.0013709583837044192, \"kl\": 0.00015598793763274443, \"top101\": 0, \"dclose\": 0.8733926963806152}, \"records\": 14}, \"E100\": {\"all\": {\"n\": 772, \"flips\": 15, \"dlogp\": -0.0027365098258605894, \"kl\": 0.010917183436414738, \"top101\": 13, \"dclose\": 4.229122434255372}, \"thought\": {\"n\": 403, \"flips\": 13, \"dlogp\": -0.0009619827490882306, \"kl\": 0.016394366567986776, \"top101\": 0, \"dclose\": 2.7708114311653684}, \"close\": {\"n\": 14, \"flips\": 1, \"dlogp\": -0.012476601228497333, \"kl\": 0.04054957357772894, \"top101\": 13, \"dclose\": -0.012476601228497333}, \"action\": {\"n\": 305, \"flips\": 1, \"dlogp\": -0.005511732649494184, \"kl\": 0.003991734373457653, \"top101\": 0, \"dclose\": 6.669067970651095}, \"delimiter\": {\"n\": 50, \"flips\": 0, \"dlogp\": 0.0026168836014403497, \"kl\": 0.0007192587123972771, \"top101\": 0, \"dclose\": 2.2870898056030273}, \"records\": 14}, \"E300\": {\"all\": {\"n\": 772, \"flips\": 40, \"dlogp\": -0.06396451131127041, \"kl\": 0.09193375289748987, \"top101\": 11, \"dclose\": 8.893344721028225}, \"thought\": {\"n\": 403, \"flips\": 34, \"dlogp\": -0.08510340193041575, \"kl\": 0.13916953680828842, \"top101\": 0, \"dclose\": 6.002988862636367}, \"close\": {\"n\": 14, \"flips\": 3, \"dlogp\": -0.1826402531868163, \"kl\": 0.22620151743779257, \"top101\": 11, \"dclose\": -0.1826402531868163}, \"action\": {\"n\": 305, \"flips\": 3, \"dlogp\": -0.04147759101918486, \"kl\": 0.03656130604690216, \"top101\": 0, \"dclose\": 13.606609375750432}, \"delimiter\": {\"n\": 50, \"flips\": 0, \"dlogp\": 0.002473958153714193, \"kl\": 0.011390284267254174, \"top101\": 0, \"dclose\": 5.9799740028381345}, \"records\": 14}}\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n[... 496 lines cut ...]\n+  if out['arms']:\n+   summary['changed']=sum(r['ids']!=b['ids'] for r,b in zip(rows,out['arms'][0]['rows']))\n+  out['arms'].append({'name':name,'adapter':path,'seconds':prev,'rows':\n[... 272 characters cut ...]"},{"i":119,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup bash /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/hold2.sh > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":120,"kind":"output","long":false,"text":" succeeded in 218ms:\n419672"},{"i":121,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100/size.json; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu033/size.json'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":122,"kind":"output","long":true,"text":" succeeded in 224ms:\n{\"edit\": {\"summary\": {\"r\": 4, \"scale\": 2.0, \"changed\": 120, \"of\": 420, \"net_rel\": 0.009999844519289671, \"rel_median\": 0.025607448442845897, \"rel_min\": 0.02559721074468111, \"rel_max\": 0.02561327673272679, \"rel_max_mod\": \"38.o_proj\", \"total_rel\": 0.025607184565155733, \"total_fro\": 20.622587976191692, \"stable_rank_median\": 2.2202454013444086, \"part_rank_median\": 3.7828769789818555, \"by_type\": {\"down_proj\": 0.02560740646650373, \"o_proj\": 0.025607560862767595}, \"by_depth\": [0.025606885395601055, 0.02560754473392491, 0.025607945766715233, 0.025606286380594225, 0.02560762327694732, 0.025607708441354397]}, \"rows\": [{\"mod\": \"0.down_proj\", \"fro\": 1.9214502447005881, \"rel\": 0.02561125430082965, \"top_rel\": 0.018126480157039573, \"stable_rank\": 1.996341049002564, \"part_rank\": 3.6672122472063093}, {\"mod\": \"0.o_proj\", \"fro\": 1.8697198831381114, \"rel\": 0.025606030784245268, \"top_rel\": 0.017688863565767713, \"stable_rank\": 2.095485509961068, \"part_rank\": 3.604288775336221}, {\"mod\": \"1.down_proj\", \"fro\": 1.8446747349716832, \"rel\": 0.02560665950479722, \"top_rel\": 0.014506494594108882, \"stable_rank\": 3.115881210172308, \"part_rank\": 3.9629948147760223}, {\"mod\": \"1.o_proj\", \"fro\": 1.9395622295319224, \"rel\": 0.025607799745979, \"top_rel\": 0.019009506962363525, \"stable_rank\": 1.814691579062183, \"part_rank\": 3.5782988660376533}, {\"mod\": \"2.down_proj\", \"fro\": 1.9547699889840289, \"rel\": 0.025606254992937373, \"top_rel\": 0.02091320710370737, \"stable_rank\": 1.499169904819231, \"part_rank\": 2.96199592536152}, {\"mod\": \"2.o_proj\", \"fro\": 1.8958382607713657, \"rel\": 0.025606870977538186, \"top_rel\": 0.016199744537660807, \"stable_rank\": 2.498599763591573, \"part_rank\": 3.869678788554157}, {\"mod\": \"3.down_proj\", \"fro\": 1.9382673985982455, \"rel\": 0.025606790860165308, \"top_rel\": 0.016774259406020623, \"stable_rank\": 2.3303631228354065, \"part_rank\": 3.785160353700936}, {\"mod\": \"3.o_proj\", \"fro\": 1.8834793676624164, \"rel\": 0.025607576587855153, \"top_rel\": 0.015733272941019515, \"stable_rank\": 2.649102770449005, \"part_rank\": 3.8721007461246426}, {\"mod\": \"4.down_proj\", \"fro\": 1.9257752769108865, \"rel\": 0.02560818613241731, \"top_rel\": 0.01506742418337074, \"stable_rank\": 2.888548114053621, \"part_rank\": 3.9471582856375877}, {\"mod\": \"4.o_proj\", \"fro\": 1.8440984155741553, \"rel\": 0.025607404226460136, \"top_rel\": 0.015494609929832584, \"stable_rank\": 2.731302606280005, \"part_rank\": 3.9239503732089434}, {\"mod\": \"5.down_proj\", \"fro\": 1.8278188655536778, \"rel\": 0.025607405690314205, \"top_rel\": 0.014847313720295914, \"stable_rank\": 2.9746467117673934, \"part_rank\": 3.9342736924335524}, {\"mod\": \"5.o_proj\", \"fro\": 1.8536385707513106, \"rel\": 0.025607634307733818, \"top_rel\": 0.01837626629638468, \"stable_rank\": 1.941888844756251, \"part_rank\": 3.6690096258905815}, {\"mod\": \"6.down_proj\", \"fro\": 1.8560157912831226, \"rel\": 0.02560756628991897, \"top_rel\": 0.01737403067323283, \"stable_rank\": 2.1723782375436107, \"part_rank\": 3.735829739464619}, {\"mod\": \"6.o_proj\", \"fro\": 1.8943604566268943, \"rel\": 0.025605696808745627, \"top_rel\": 0.017667341719963845, \"stable_rank\": 2.100539144396381, \"part_rank\": 3.759517702543781}, {\"mod\": \"7.down_proj\", \"fro\": 1.8874655806465181, \"rel\": 0.025604277321852775, \"top_rel\": 0.01827075783204416, \"stable_rank\": 1.963866320299273, \"part_rank\": 3.600054486914287}, {\"mod\": \"7.o_proj\", \"fro\": 1.9122850209913909, \"rel\": 0.025608085957775147, \"top_rel\": 0.018884866335719088, \"stable_rank\": 1.8387657564409592, \"part_rank\": 3.5688279207051825}, {\"mod\": \"8.down_proj\", \"fro\": 1.9550740529823813, \"rel\": 0.025606899813663923, \"top_rel\": 0.019174816202523814, \"stable_rank\": 1.7834115915706732, \"part_rank\": 3.582282005892869}, {\"mod\": \"8.o_proj\", \"fro\": 1.8754435141968124, \"rel\": 0.025606842853567208, \"top_rel\": 0.019027412645799515, \"stable_rank\": 1.811142404819007, \"part_rank\": 3.610124009796471}, {\"mod\": \"9.down_proj\", \"fro\": 1.9669966651755557, \"rel\": 0.02560586919528515, \"top_rel\": 0.01707827522189498, \"stable_rank\": 2.2479726811059124, \"part_rank\": 3.82193503\n[... 85714 characters cut ...]"},{"i":123,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/rebuild.py turn10/verify_rebuild.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":124,"kind":"output","long":false,"text":" succeeded in 296ms:"},{"i":125,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/verify_rebuild.py 100 > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/verify100.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":126,"kind":"output","long":false,"text":" succeeded in 206ms:\n421917"},{"i":127,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'nohup /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/verify_rebuild.py 033 > /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/verify033.log 2>&1 < /dev/null & echo \"'$!'\"'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":128,"kind":"output","long":false,"text":" succeeded in 217ms:\n422007"},{"i":129,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -7 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":130,"kind":"output","long":true,"text":" succeeded in 221ms:\nREPLAY cpu100_edit\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n[... 514 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Estimating runtime and resources**"},{"i":131,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100_edit_replay.log; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2_started.json'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":132,"kind":"output","long":true,"text":" succeeded in 208ms:\n },\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n}\n{\"start\": 1794665918.5473034, \"limit\": 1500, \"pid\": 419674}\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n[... 1084 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":133,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/freeze_sources.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":134,"kind":"output","long":false,"text":" succeeded in 301ms:"},{"i":135,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/freeze_sources.py; tail -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; tail -2 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/verify100.log; tail -2 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/verify033.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":136,"kind":"output","long":true,"text":" succeeded in 1715ms:\nFROZEN 99 files capture_bytes 325211847 maps ddf8637741b3f16b75c10c6b826e3fa9d3f13a0f05b16408791b959648838811\nREPLAY cpu100_edit\nREPLAY cpu033_edit\nREPLAY cpu100_ctrl\n09:20:07 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/rebuilt100/edit 0.0099999997806608 120\n09:20:07 BUILD /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/rebuilt033/edit 0.0033000000860908046 120\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n[... 1132 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":137,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/check_progress.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":138,"kind":"output","long":false,"text":" succeeded in 277ms:"},{"i":139,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/check_progress.py; tail -6 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":140,"kind":"output","long":true,"text":" succeeded in 243ms:\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nBIT_EXACT 100 6\nBIT_EXACT 033 6\nSIZE 100 {'edit': {'net_rel': 0.009999844519289671, 'changed': 120, 'rel_max': 0.02561327673272679, 'stable_rank_median': 2.2202454013444086}, 'ctrl': {'net_rel': 0.009999844519289671, 'changed': 120, 'rel_max': 0.02561327673272679, 'stable_rank_median': 2.2202454013444086}}\nSIZE 033 {'edit': {'net_rel': 0.0032999601021971347, 'changed': 120, 'rel_max': 0.00845275934312434, 'stable_rank_median': 2.2199279514647148}, 'ctrl': {'net_rel': 0.0032999601021971347, 'changed': 120, 'rel_max': 0.00845275934312434, 'stable_rank_median': 2.2199279514647148}}\nREPLAY cpu100_edit\nREPLAY cpu033_edit\nREPLAY cpu100_ctrl\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n[... 574 lines cut ...]\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Analyzing log and validation details**\n**Reviewing tool usage and script policies**\n**Analyzing CPU process and data integrity**\n**Verifying program classification syntax**\n**Analyzing tool schema inconsistencies**\n**Verifying initial fit examples**"},{"i":141,"kind":"assistant","long":false,"text":"[line removed by the dashboard scrubber]"},{"i":142,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -9 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/check_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":143,"kind":"output","long":true,"text":" succeeded in 244ms:\nREPLAY cpu100_edit\nREPLAY cpu033_edit\nREPLAY cpu100_ctrl\nREPLAY cpu033_ctrl\nSERVER_BUDGET 1281\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nBIT_EXACT 100 6\nBIT_EXACT 033 6\nSIZE 100 {'edit': {'net_rel': 0.009999844519289671, 'changed': 120, 'rel_max': 0.02561327673272679, 'stable_rank_median': 2.2202454013444086}, 'ctrl': {'net_rel': 0.009999844519289671, 'changed': 120, 'rel_max': 0.02561327673272679, 'stable_rank_median': 2.2202454013444086}}\nSIZE 033 {'edit': {'net_rel': 0.0032999601021971347, 'changed': 120, 'rel_max': 0.00845275934312434, 'stable_rank_median': 2.2199279514647148}, 'ctrl': {'net_rel': 0.0032999601021971347, 'changed': 120, 'rel_max': 0.00845275934312434, 'stable_rank_median': 2.2199279514647148}}\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n[... 1178 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":144,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/audit_evaluation.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":145,"kind":"output","long":false,"text":" succeeded in 263ms:"},{"i":146,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/audit_evaluation.py; tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":147,"kind":"output","long":true,"text":" succeeded in 283ms:\n{\n  \"eval_calls.jsonl\": {\n    \"records\": 14,\n    \"tasks\": 11,\n    \"boundary_violations\": []\n  },\n  \"generation_panel.jsonl\": {\n    \"records\": 112,\n    \"tasks\": 52,\n    \"boundary_violations\": []\n  },\n  \"replay_panel.jsonl\": {\n    \"records\": 8,\n    \"tasks\": 8,\n    \"boundary_violations\": []\n  }\n}\nREPLAY cpu100_ctrl\nREPLAY cpu033_ctrl\n[... 597 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Reviewing code audit and update timing**"},{"i":148,"kind":"assistant","long":false,"text":"Replay is complete for both edits and controls. The serving wrapper has started the continuation checks: 100 later-call syntax contexts and 12 whole turns, shared across all arms. The data audit found no stage-2 overlap in the fit or pre-test panels."},{"i":149,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; wc -w /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":150,"kind":"output","long":true,"text":" succeeded in 216ms:\nREPLAY cpu100_ctrl\nREPLAY cpu033_ctrl\nSERVER_BUDGET 1281\nserver up after 72s (pid/pgid 425976, log /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/logs/server_18410_1114_092136.log)\nPANEL 112 52\n344 /home/keith/gemma-v2/wsp31/authors/gpt/NOTES.md\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n[... 583 lines cut ...]\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Designing finalization script workflow**\n\nI\u2019m organizing a script that monitors task completion across multiple arms, ensuring the first entry finishes fully before the second starts, with a controlled queue handling readiness states. The finalizer loads generation data, runs syntax checks with error handling, and writes atomic snapshots to ensure stable updates."},{"i":151,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -100 /home/keith/gemma-v2/wsp31/interp/toolcall_check.py; tail -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":152,"kind":"output","long":true,"text":" succeeded in 235ms:\n    return dict(episodes=len(eps), answers=sum(len(e) for e in eps), tool_calls=n, unpaired=k, eps_unpaired=ek,\n                multi=any(len(e) > 1 for e in eps), long_thoughts=long_n, loops=loops)\n\n\ndef tail(k, n, p):\n    \"\"\"P(X >= k) for X binomial(n, p).\"\"\"\n    if k <= 0:\n        return 1.0\n    lg = math.lgamma\n    return min(1.0, sum(math.exp(lg(n + 1) - lg(i + 1) - lg(n - i + 1) + i * math.log(p) + (n - i) * math.log(1 - p))\n                        for i in range(k, n + 1)))\n\n\ndef verdict(m, hi, ep_hi):\n    n, k = m[\"tool_calls\"], m[\"unpaired\"]\n    if n and k / n >= MARK and tail(k, n, hi) <= TAIL and \\\n            (not m[\"multi\"] or tail(m[\"eps_unpaired\"], m[\"episodes\"], ep_hi) <= TAIL):\n        return \"BROKEN\"\n    if n >= NMIN and k / n < MARK:\n[... 1409 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":153,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/finalize.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":154,"kind":"output","long":false,"text":" succeeded in 288ms:"},{"i":155,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -7 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":156,"kind":"output","long":true,"text":" succeeded in 205ms:\nPANEL 112 52\nPROGRESS reference 25 60.0\nPROGRESS reference 50 75.9\nPROGRESS reference 75 105.5\nPROGRESS reference 100 128.7\n[line removed by the dashboard scrubber]\nPROGRESS cpu100_edit 25 62.4\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n[... 711 lines cut ...]\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Analyzing model output diagnostics**\n**Reviewing prediction range discrepancies**\n**Verifying pretest and finalizer processes**\n**Analyzing generation and testing limitations**"},{"i":157,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"Get-Content turn10/finalize.py | Select-String -Pattern 'source_names|Data selection|These checks'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":158,"kind":"output","long":false,"text":" succeeded in 72ms:\n\nsource_names=['outcome_map.py','rebuild.py','prepare.py','pairs.jsonl','maps.pt','capture_stats.pt','selection.json','f\nit_diagnostics.json','generation_panel.jsonl','replay_panel.jsonl','eval_calls.jsonl','environment.json','tools_sha256.\njson']\nhs={n:sha(C/n) for n in source_names};hs.update({'tools/'+str(p.relative_to(C/'tools')):sha(p) for p in \n(C/'tools').rglob('*') if p.is_file() and '__pycache__' not in p.parts})\nData selection (`code/turn10/prepare.py`): unedited base/aa request logs from b007, x001, x003, x004 and x005. Keep \ntasks in both stage-1 lists and exclude all stage-2 list overlaps; audits checked nine lists. In each episode take the \n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nlength, then batch/arm names. Reserve tasks with SHA256(task) modulo 4 equal to zero; sort by hash. This yielded 18 \n[line removed by the dashboard scrubber]\nare in `pairs.jsonl` and `selection.json`.\nThese checks can exclude a large local syntax break; they do not test full-episode looping, total tool use or patch \ncorrectness. The dose choice uses these panels, so they are development checks. The custom transport capture/scout \ncode is new; g31 and the official replay backend are documented as verified, but the transport-to-solve-rate link is \nunvalidated."},{"i":159,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -7 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/check_progress.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":160,"kind":"output","long":true,"text":" succeeded in 243ms:\nPROGRESS reference 75 105.5\nPROGRESS reference 100 128.7\n[line removed by the dashboard scrubber]\nPROGRESS cpu100_edit 25 62.4\nPROGRESS cpu100_edit 50 74.5\nPROGRESS cpu100_edit 75 106.0\nPROGRESS cpu100_edit 100 132.0\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\nBIT_EXACT 100 6\nBIT_EXACT 033 6\nSIZE 100 {'edit': {'net_rel': 0.009999844519289671, 'changed': 120, 'rel_max': 0.02561327673272679, 'stable_rank_median': 2.2202454013444086}, 'ctrl': {'net_rel': 0.009999844519289671, 'changed': 120, 'rel_max': 0.02561327673272679, 'stable_rank_median': 2.2202454013444086}}\nSIZE 033 {'edit': {'net_rel': 0.0032999601021971347, 'changed': 120, 'rel_max': 0.00845275934312434, 'stable_rank_median': 2.2199279514647148}, 'ctrl': {'net_rel': 0.0032999601021971347, 'changed': 120, 'rel_max': 0.00845275934312434, 'stable_rank_median': 2.2199279514647148}}\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\n[... 1445 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":161,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/finalize.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":162,"kind":"output","long":false,"text":" succeeded in 270ms:"},{"i":163,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/cpu100_edit_replay.json; tail -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":164,"kind":"output","long":true,"text":" succeeded in 217ms:\n{\n \"probeset\": \"/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/replay_panel.jsonl\",\n \"calls\": 8,\n \"episodes\": 8,\n[line removed by the dashboard scrubber]\n \"base_seconds\": 34.1,\n \"base\": {\n  \"solved\": {\n   \"calls\": 4,\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n[line removed by the dashboard scrubber]\n   \"mean_logprob_think\": -0.07958,\n   \"mean_logprob_action\": -0.07637,\n   \"mean_logprob_all\": -0.07763,\n   \"top_is_logged\": 0.99288,\n   \"calls_without_divergence\": 0.5,\n   \"first_divergence_in_think\": 0,\n   \"first_divergence_in_action\": 2,\n[... 784 lines cut ...]\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Analyzing tool run and submission consistency**\n**Analyzing model divergence causes**"},{"i":165,"kind":"assistant","long":true,"text":"The 1% edit produced 100/100 well-formed after-close calls and 12/12 well-formed whole turns, with no repetition or length cuts. It changed 30 of the 112 continuations. The reference was 100/100 and 11/12. The smaller dose and controls are still running.\n\napply patch\npatch: completed\nC:\\Users\\Owner\\wsp31_loop\\work\\gpt\\turn10\\inspect_generations.py\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/audit_evaluation.py b/turn10/audit_evaluation.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..bf360c8887ce7dca05496d8f998c08114b332cd8\n--- /dev/null\n+++ b/turn10/audit_evaluation.py\n@@ -0,0 +1,9 @@\n+from pathlib import Path\n+import json\n+R=Path('/home/keith/gemma-v2');C=R/'wsp31/authors/gpt/code/turn10';sets=R/'wsp31/queue/sets'\n+allow=set((sets/'stage1_ids.txt').read_text().split());deny=set().union(*(set(p.read_text().split()) for p in sets.glob('stage2_ids*.txt')))\n+out={}\n+for fn in ['eval_calls.jsonl','generation_panel.jsonl','replay_panel.jsonl']:\n+ rs=[json.loads(l) for l in (C/fn).open()];bad=sorted({r['instance'] for r in rs if r['instance'] not in allow or r['instance'] in deny})\n+ out[fn]={'records':len(rs),'tasks':len({r['instance'] for r in rs}),'boundary_violations':bad};assert not bad,(fn,bad)\n+print(json.dumps(out,indent=2));(C/'evaluation_boundary_audit.json').write_text(json.dumps(out,indent=2))\ndiff --git a/turn10/check_progress.py b/turn10/check_progress.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..5747612f3c142a44a1bf3d079cb873465c054c7e\n--- /dev/null\n+++ b/turn10/check_progress.py\n@@ -0,0 +1,15 @@\n+import json\n+from pathlib import Pa\n[... 39942 characters cut ...]"},{"i":166,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/inspect_generations.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":167,"kind":"output","long":false,"text":" succeeded in 268ms:"},{"i":168,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/inspect_generations.py; tail -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":169,"kind":"output","long":true,"text":" succeeded in 3620ms:\nARM cpu100_edit tool_name_changes 3\nCONTEXT [task] 26 after 4/30 used). Finalize your edits and call submit_patch soon.\"}<|\"|>}<tool_response|><|channel>thought\nThe diff is there. I don't know why `submit_patch` said `files_changed: 1`, but maybe it's just a summary.\n\nI'll call `submit_patch` again just to be sure.\n\n<channel|><|tool_call>call:submit_patch{}<tool_call|><|tool_response>response:submit_patch{value:<|\"|>{\"status\": \"ok\", \"patch_size\": 444, \"files_changed\": 1}<|\"|>}<tool_response|><|channel>thought\nStill says 1. I suspect it's because it's ignoring the `tests/` directory in its count.\n\nI'm confident in the fix.\n\n<channel|>\nBASE <|tool_call>call:run_command{command:<|\"|>git checkout -- tests/test_env.py<|\"|>}<tool_call|><|tool_response>\nEDIT <|tool_call>call:submit_patch{}<tool_call|><|tool_response>\nCONTEXT [task] 2 turn _char(line, char):\\n            return self._lines[line - 1][char - 1]\\n\\n        # Find the semicolon\\n        while current_char(line, char) != \\\";\\\":\\n            assert self.WHITESPACE_RE.match(current_char(line, char))\\n            line, char = self._previous_char(line, char)\\n        # Skip it\\n        line, char = self._previous_char(line, char)\\n        # Skip the whitespace and table/feature name\", \"start_line\": 370, \"end_line\": 420, \"total_lines\": 681, \"is_truncated\": false}<|\"|>}<tool_response|>\nBASE <|channel>thought\nThe traceback said:\n`File \"/Users/cjdunn/env_gtools/lib/python3.7/site-packages/glyphsLib/builder/features.py\", line 396, in _build_end_locations_rec`\n`previous_in_block = st.statements[-1]`\n[... 1591 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":170,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/finish_turn.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":171,"kind":"output","long":false,"text":" succeeded in 271ms:"},{"i":172,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":173,"kind":"output","long":true,"text":" succeeded in 213ms:\n[line removed by the dashboard scrubber]\nPROGRESS cpu033_edit 25 61.5\nPROGRESS cpu033_edit 50 78.5\nPROGRESS cpu033_edit 75 106.5\nPROGRESS cpu033_edit 100 131.3\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n[... 790 lines cut ...]\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Monitoring generation progress**\n**Configuring computation environment**"},{"i":174,"kind":"assistant","long":true,"text":"The smaller edit has finished its 100 after-close contexts; the whole-turn checks are finishing now. Both independent rebuilds matched all six required files exactly. I\u2019m keeping the 3% scout out of the queue because it failed the thought-ending check.\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/audit_evaluation.py b/turn10/audit_evaluation.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..bf360c8887ce7dca05496d8f998c08114b332cd8\n--- /dev/null\n+++ b/turn10/audit_evaluation.py\n@@ -0,0 +1,9 @@\n+from pathlib import Path\n+import json\n+R=Path('/home/keith/gemma-v2');C=R/'wsp31/authors/gpt/code/turn10';sets=R/'wsp31/queue/sets'\n+allow=set((sets/'stage1_ids.txt').read_text().split());deny=set().union(*(set(p.read_text().split()) for p in sets.glob('stage2_ids*.txt')))\n+out={}\n+for fn in ['eval_calls.jsonl','generation_panel.jsonl','replay_panel.jsonl']:\n+ rs=[json.loads(l) for l in (C/fn).open()];bad=sorted({r['instance'] for r in rs if r['instance'] not in allow or r['instance'] in deny})\n+ out[fn]={'records':len(rs),'tasks':len({r['instance'] for r in rs}),'boundary_violations':bad};assert not bad,(fn,bad)\n+print(json.dumps(out,indent=2));(C/'evaluation_boundary_audit.json').write_text(json.dumps(out,indent=2))\ndiff --git a/turn10/check_progress.py b/turn10/check_progress.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..5747612f3c142a44a1bf3d079cb873465c054c7e\n--- /dev/null\n+++ b/turn10/check_progress.py\n@@ -0,0 +1,15 @@\n+import json\n+from pathlib import Path\n+A=Path('/home/keith/gemma-v2/wsp31/authors/gpt');S=A/'scratch/turn10';C=A/'code/turn10'\n+for\n[... 44878 characters cut ...]"},{"i":175,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -7 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; cat /home/keith/gemma-v2/wsp31/queue/CHAMPION.md'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":176,"kind":"output","long":true,"text":" succeeded in 219ms:\nPROGRESS cpu033_edit 25 61.5\nPROGRESS cpu033_edit 50 78.5\nPROGRESS cpu033_edit 75 106.5\nPROGRESS cpu033_edit 100 131.3\n[line removed by the dashboard scrubber]\nPROGRESS cpu100_ctrl 25 62.4\nPROGRESS cpu100_ctrl 50 73.2\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\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n[... 799 lines cut ...]\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Analyzing script compilation and timing**\n**Reviewing parked tasks and stable records**\n**Noting script wrapping and build details**"},{"i":177,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"python -c \\\"import ast,pathlib; paths=[pathlib.Path('turn10/finalize.py'),pathlib.Path('turn10/finish_turn.py')]; [ast.parse(p.read_text()) for p in paths]; print('Parsed both finalization scripts')\\\"\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":178,"kind":"output","long":false,"text":" succeeded in 54ms:\nParsed both finalization scripts"},{"i":179,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -4 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":180,"kind":"output","long":true,"text":" succeeded in 231ms:\n[line removed by the dashboard scrubber]\nPROGRESS cpu100_ctrl 25 62.4\nPROGRESS cpu100_ctrl 50 73.2\nPROGRESS cpu100_ctrl 75 104.5\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n[... 788 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Wrapping up final edits**"},{"i":181,"kind":"assistant","long":true,"text":"Both edits finished with 100/100 well-formed after-close calls and 12/12 whole turns. Neither showed repetition or length cuts. The 0.33% edit changed 25 continuations; the 1% edit changed 30. I\u2019ll finish the control checks, then create the first READY file before assembling the second entry.\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/audit_evaluation.py b/turn10/audit_evaluation.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..bf360c8887ce7dca05496d8f998c08114b332cd8\n--- /dev/null\n+++ b/turn10/audit_evaluation.py\n@@ -0,0 +1,9 @@\n+from pathlib import Path\n+import json\n+R=Path('/home/keith/gemma-v2');C=R/'wsp31/authors/gpt/code/turn10';sets=R/'wsp31/queue/sets'\n+allow=set((sets/'stage1_ids.txt').read_text().split());deny=set().union(*(set(p.read_text().split()) for p in sets.glob('stage2_ids*.txt')))\n+out={}\n+for fn in ['eval_calls.jsonl','generation_panel.jsonl','replay_panel.jsonl']:\n+ rs=[json.loads(l) for l in (C/fn).open()];bad=sorted({r['instance'] for r in rs if r['instance'] not in allow or r['instance'] in deny})\n+ out[fn]={'records':len(rs),'tasks':len({r['instance'] for r in rs}),'boundary_violations':bad};assert not bad,(fn,bad)\n+print(json.dumps(out,indent=2));(C/'evaluation_boundary_audit.json').write_text(json.dumps(out,indent=2))\ndiff --git a/turn10/check_progress.py b/turn10/check_progress.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..5747612f3c142a44a1bf3d079cb873465c054c7e\n--- /dev/null\n+++ b/turn10/check_progress.py\n@@ -0,0 +1,15 @@\n+import json\n+from pathlib import Path\n+A=Path('/home/keith/gemma-v2/wsp31/authors/gpt');S=\n[... 44919 characters cut ...]"},{"i":182,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -5 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":183,"kind":"output","long":true,"text":" succeeded in 210ms:\nPROGRESS cpu100_ctrl 25 62.4\nPROGRESS cpu100_ctrl 50 73.2\nPROGRESS cpu100_ctrl 75 104.5\nPROGRESS cpu100_ctrl 100 132.8\n[line removed by the dashboard scrubber]\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n[... 789 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Finalizing parity run check**"},{"i":184,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/finalize.py 100'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":185,"kind":"output","long":false,"text":" succeeded in 543ms:\nPREPARED paired-outcome-writers-r4-100 record words 1683 syntax {'reference': 'NOT BROKEN', 'cpu100_edit': 'NOT BROKEN', 'cpu100_ctrl': 'NOT BROKEN'}"},{"i":186,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'head -32 /home/keith/gemma-v2/wsp31/authors/gpt/queue/paired-outcome-writers-r4-100/record.md; tail -10 /home/keith/gemma-v2/wsp31/authors/gpt/queue/paired-outcome-writers-r4-100/record.md; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/syntax.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":187,"kind":"output","long":true,"text":" succeeded in 225ms:\ntitle: Paired outcome writer map across all 60 layers at 1 percent\n\n## Hypothesis\n\n[line removed by the dashboard scrubber]\n\nThis differs from 0025/0026's code-versus-prose projection and 0035/0036's constant instruction writes. It uses outcome-labelled, within-task pairs, separate input and output factors, and a ridge solve with preserve samples. It neither projects onto a thought-close direction nor replaces a neuron. The E4B patch-correctness direction failed; this version tests paired tasks and a conditional map across both writers in every layer. That difference warrants a test, not a claim that correctness is readable.\n\n[line removed by the dashboard scrubber]\n\n## Exact recipe\n\nbase: champion generation 0\nsize: whole network 0.999984% over 120 matrices, largest matrix 2.561328%\ncontrol size: whole network 0.999984% over 120 matrices, largest matrix 2.561328%\n\nRank 4, alpha 8, bf16 LoRA factors, o_proj and down_proj in layers 0 through 59. Median stable rank 2.2202. The norm uses all 420 editable matrices as its denominator. No champion overlap exists at design. A future writer edit could add to or oppose this map; no stack benefit is assumed.\n\n[line removed by the dashboard scrubber]\n[... 847 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Preparing technical review notes**"},{"i":188,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/finalize.py 100 --ready; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/finish_turn.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":189,"kind":"output","long":true,"text":" succeeded in 1968ms:\nREADY paired-outcome-writers-r4-100 2026-11-14T14:34:07.922255+00:00\n{\n  \"utc\": \"2026-11-14T14:34:07.987046+00:00\",\n  \"ready\": [\n    \"paired-outcome-writers-r4-100\"\n  ],\n  \"gpu_seconds\": 698.0301401615143,\n  \"gpu_holds\": [\n    {\n      \"start\": 1794665179.3569732,\n      \"end\": 1794665877.3871129,\n      \"seconds\": 698.0301401615143\n    }\n  ],\n  \"sizes\": {\n    \"100\": {\n      \"r\": 4,\n      \"scale\": 2.0,\n      \"changed\": 120,\n[... 829 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Analyzing generation readiness and control flow**"},{"i":190,"kind":"assistant","long":true,"text":"`paired-outcome-writers-r4-100` is complete with READY. It contains the matched control, recipe, prediction, hashes, and rebuild receipt. The smaller entry is waiting on its control\u2019s last continuation checks.\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/audit_evaluation.py b/turn10/audit_evaluation.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..bf360c8887ce7dca05496d8f998c08114b332cd8\n--- /dev/null\n+++ b/turn10/audit_evaluation.py\n@@ -0,0 +1,9 @@\n+from pathlib import Path\n+import json\n+R=Path('/home/keith/gemma-v2');C=R/'wsp31/authors/gpt/code/turn10';sets=R/'wsp31/queue/sets'\n+allow=set((sets/'stage1_ids.txt').read_text().split());deny=set().union(*(set(p.read_text().split()) for p in sets.glob('stage2_ids*.txt')))\n+out={}\n+for fn in ['eval_calls.jsonl','generation_panel.jsonl','replay_panel.jsonl']:\n+ rs=[json.loads(l) for l in (C/fn).open()];bad=sorted({r['instance'] for r in rs if r['instance'] not in allow or r['instance'] in deny})\n+ out[fn]={'records':len(rs),'tasks':len({r['instance'] for r in rs}),'boundary_violations':bad};assert not bad,(fn,bad)\n+print(json.dumps(out,indent=2));(C/'evaluation_boundary_audit.json').write_text(json.dumps(out,indent=2))\ndiff --git a/turn10/check_progress.py b/turn10/check_progress.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..5747612f3c142a44a1bf3d079cb873465c054c7e\n--- /dev/null\n+++ b/turn10/check_progress.py\n@@ -0,0 +1,15 @@\n+import json\n+from pathlib import Path\n+A=Path('/home/keith/gemma-v2/wsp31/authors/gpt');S=A/'scratch/turn10';C=A/'code/turn10'\n+for nm in ['cpu100_edit','cpu033_edit','cpu100\n[... 44835 characters cut ...]"},{"i":191,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -6 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; ls /home/keith/gemma-v2/wsp31/authors/gpt/queue/paired-outcome-writers-r4-100'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":192,"kind":"output","long":true,"text":" succeeded in 190ms:\nPROGRESS cpu100_ctrl 50 73.2\nPROGRESS cpu100_ctrl 75 104.5\nPROGRESS cpu100_ctrl 100 132.8\n[line removed by the dashboard scrubber]\nPROGRESS cpu033_ctrl 25 62.7\nPROGRESS cpu033_ctrl 50 77.6\nREADY\nbuild.sh\nchecks.json\nctrl\nedit\nrebuild_receipt.json\nrecord.md\nsize.json\nsource_hashes.json\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n[... 1612 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":193,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'tail -7 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2.log; cat /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/hold2_finished.json'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":194,"kind":"output","long":true,"text":" succeeded in 234ms:\nPROGRESS cpu033_ctrl 50 77.6\nPROGRESS cpu033_ctrl 75 106.9\nPROGRESS cpu033_ctrl 100 131.4\n[line removed by the dashboard scrubber]\nDONE 806.7\ncmd rc=0\nserver 425976 stopped at 09:36:21, hold 885s\n{\"start\": 1794665918.5473034, \"end\": 1794666981.5439312, \"seconds\": 1062.9966280460358, \"returncode\": 0}\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n[... 791 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Confirming task progress**"},{"i":195,"kind":"assistant","long":false,"text":"All continuation checks are complete, and the wrapper has stopped the server. Both edits passed the syntax check; the controls stayed below its 3% threshold. I\u2019m completing the second entry and checking the final files and GPU time."},{"i":196,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/finalize.py 033'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":197,"kind":"output","long":false,"text":" succeeded in 604ms:\nPREPARED paired-outcome-writers-r4-033 record words 1683 syntax {'reference': 'NOT BROKEN', 'cpu033_edit': 'NOT BROKEN', 'cpu033_ctrl': 'NOT BROKEN'}"},{"i":198,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 'head -17 /home/keith/gemma-v2/wsp31/authors/gpt/queue/paired-outcome-writers-r4-033/record.md; tail -8 /home/keith/gemma-v2/wsp31/authors/gpt/queue/paired-outcome-writers-r4-033/record.md; tail -8 /home/keith/gemma-v2/wsp31/authors/gpt/scratch/turn10/syntax.log'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":199,"kind":"output","long":true,"text":" succeeded in 224ms:\ntitle: Paired outcome writer map across all 60 layers at 0.33 percent\n\n## Hypothesis\n\n[line removed by the dashboard scrubber]\n\nThis differs from 0025/0026's code-versus-prose projection and 0035/0036's constant instruction writes. It uses outcome-labelled, within-task pairs, separate input and output factors, and a ridge solve with preserve samples. It neither projects onto a thought-close direction nor replaces a neuron. The E4B patch-correctness direction failed; this version tests paired tasks and a conditional map across both writers in every layer. That difference warrants a test, not a claim that correctness is readable.\n\n[line removed by the dashboard scrubber]\n\n## Exact recipe\n\nbase: champion generation 0\nsize: whole network 0.329996% over 120 matrices, largest matrix 0.845276%\ncontrol size: whole network 0.329996% over 120 matrices, largest matrix 0.845276%\n\nRank 4, alpha 8, bf16 LoRA factors, o_proj and down_proj in layers 0 through 59. Median stable rank 2.2199. The norm uses all 420 editable matrices as its denominator. No champion overlap exists at design. A future writer edit could add to or oppose this map; no stack benefit is assumed.\n\n## Prediction (written before the run)\n[... 817 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Verifying record consistency**"},{"i":200,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/finalize.py 033 --ready; /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/finish_turn.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":201,"kind":"output","long":true,"text":" succeeded in 2612ms:\nREADY paired-outcome-writers-r4-033 2026-11-14T14:37:00.491436+00:00\n{\n  \"utc\": \"2026-11-14T14:37:01.094848+00:00\",\n  \"ready\": [\n    \"paired-outcome-writers-r4-100\",\n    \"paired-outcome-writers-r4-033\"\n  ],\n  \"gpu_seconds\": 1761.02676820755,\n  \"gpu_holds\": [\n    {\n      \"start\": 1794665179.3569732,\n      \"end\": 1794665877.3871129,\n      \"seconds\": 698.0301401615143\n    },\n    {\n      \"start\": 1794665918.5473034,\n      \"end\": 1794666981.5439312,\n      \"seconds\": 1062.9966280460358,\n      \"returncode\": 0\n[... 1701 lines cut ...]\n+t=time.time();subprocess.run([str(PY),str(C/'rebuild.py'),str(dst),'--dose',str(d)],check=True)\n+out={'seconds':time.time()-t,'files':{}}\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)"},{"i":202,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command 'scp turn10/final_audit.py wrx90:/home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/' in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":203,"kind":"output","long":false,"text":" succeeded in 266ms:"},{"i":204,"kind":"tool","long":false,"text":"\"C:\\\\WINDOWS\\\\System32\\\\WindowsPowerShell\\\\v1.0\\\\powershell.exe\" -Command \"ssh -o BatchMode=yes wrx90 '/home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/authors/gpt/code/turn10/final_audit.py'\" in C:\\Users\\Owner\\wsp31_loop\\work\\gpt"},{"i":205,"kind":"output","long":true,"text":" succeeded in 764ms:\n{\n  \"paired-outcome-writers-r4-100\": {\n    \"READY_utc\": \"2026-11-14T14:34:07.920860+00:00\",\n    \"pinned_sources_checked\": 99\n  },\n  \"paired-outcome-writers-r4-033\": {\n    \"READY_utc\": \"2026-11-14T14:37:00.489544+00:00\",\n    \"pinned_sources_checked\": 99\n  },\n  \"new_entries\": 2,\n  \"gpu_seconds\": 1761.02676820755,\n  \"owned_gpu_processes_active\": [],\n  \"scratch_GiB\": 3.8276606192812324,\n  \"notes_words\": 421\n}\n\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n[... 824 lines cut ...]\n+for arm in ['edit','ctrl']:\n+ for fn in ['adapter_config.json','adapter_model.safetensors','edit.json']:\n+  h1=hashlib.sha256((src/arm/fn).read_bytes()).hexdigest();h2=hashlib.sha256((dst/arm/fn).read_bytes()).hexdigest()\n+  assert h1==h2,(arm,fn,h1,h2)\n+  out['files'][arm+'/'+fn]=h1\n+(C/('rebuild_receipt_'+nm+'.json')).write_text(json.dumps(out,indent=2));print('REBUILD BIT EXACT',nm,round(time.time()-t,2),flush=True)\n\n**Summarizing test results concisely**"},{"i":206,"kind":"assistant","long":true,"text":"Queued `paired-outcome-writers-r4-100` at 1%.  \nQueued `paired-outcome-writers-r4-033` at 0.33%.  \nBoth target better patch choices through paired-outcome maps with matched controls.  \nBoth have READY files, verified rebuilds, replay results, and passed syntax checks; gains remain untested.  \n`NOTES.md` is current. GPU 0 released after 29.35 minutes of use.\ndiff --git a/turn10/audit.py b/turn10/audit.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..25d6f06286cc28d41a68c29ac217f43ef92f0cfd\n--- /dev/null\n+++ b/turn10/audit.py\n@@ -0,0 +1,34 @@\n+from pathlib import Path\n+import json,hashlib,sys\n+R=Path('/home/keith/gemma-v2');A=R/'wsp31/authors/gpt';C=A/'code/turn10';S=A/'scratch/turn10'\n+pairs=[json.loads(l) for l in (C/'pairs.jsonl').open()]\n+allow=set((R/'wsp31/queue/sets/stage1_ids.txt').read_text().split())\n+denies={p.name:set(p.read_text().split()) for p in (R/'wsp31/queue/sets').glob('stage2_ids*.txt')}\n+for p in pairs:\n+ assert p['instance'] in allow\n+ assert all(p['instance'] not in ids for ids in denies.values()),p['instance']\n+ assert p['pos']['resolved'] and not p['neg']['resolved']\n+ assert p['pos']['tool']==p['neg']['tool']\n+ for s in ['pos','neg']:\n+  r=p[s];assert r['instance']==p['instance'];assert r['ids'][r['start']:]==r['comp']\n+  assert r['request_sha256']==hashlib.sha256(Path(r['request']).read_bytes()).hexdigest()\n+  assert all(r['start']<=i<r['start']+r['comp'].index(101) for i in r['thought_pos'])\n+print('BOUNDARY PASS',len(pairs),'tasks',len(pairs)*2,'episodes',len(denies),'stage2 exclusion lists')\n+(C/'boundary_audit.json').write_text(json.dumps({'tasks':len(pairs),'episodes':len(pairs)*2,'stage2_exclusion_lists':list(denies),'passed':True},indent=2))\n+old=(A/'NOTES.md').read_text()\n+(A/'NOTES.md').write_text('''# Author gpt - turn 10 in progress\n+\n+Started 2026-11-14 14:00 UTC; deadline 15:30 UTC. Champion generation 0. Source-grounding ICV doses 3/1 were null (-2.5/-3.5). Their apparent edit-error reduction was mainly malformed calls and within baseline variation. Do not repeat forced thought closing or constant source grounding.\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+\n[line removed by the dashboard scrubber]\n+''')\n+# Read all remaining ledger hypotheses, retaining no stage-2 per-task data.\n+for p in sorted((R/'tii-wsp31-doc/research/wsp31/ledger').glob('*.md')):\n+ if p.name[:4] in ['0007','0008','0009','0010','0011','0012','0013','0015','0016','0017','0018','0020','0021','0022','0023','0026','0027','0028']:\n+  txt=p.read_text();a=txt.find('## Hypothesis');b=txt.find('## Exact recipe')\n+  print('\\nLEDGER',p.name,'\\n',txt[a:b][:3000])\n+rep=(R/'wsp31/interp/REPORT.md').read_text().splitlines();print('\\n'.join(rep[399:454]))\ndiff --git a/turn10/audit_evaluation.py b/turn10/audit_evaluation.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..bf360c8887ce7dca05496d8f998c08114b332cd8\n--- /dev/null\n+++ b/turn10/audit_evaluation.py\n@@ -0,0 +1,9 @@\n+from pathlib import Path\n+import json\n+R=Path('/home/keith/gemma-v2');C=R/'wsp31/authors/gpt/code/turn10';sets=R/'wsp31/queue/sets'\n+allow=set((sets/'stage1_ids.txt').read_text().split());deny=set().union(*(set(p.read_text().split()) for p in sets.glob('stage2_ids*.txt')))\n+out={}\n+for fn in ['eval_calls.jsonl','generation_panel.jsonl','replay_panel.jsonl']:\n+ rs=[json.loads(l) for l in (C/fn).open()];bad=sorted({r['instance'] for r in rs if r['instance'] not in allow or r['instance'] in deny})\n+ out[fn]={'records':len(rs),'tasks':len({r['instance'] for r in rs}),'boundary_violations':bad};assert not bad,(fn,bad)\n+print(json.dumps(out,indent=2));(C/'evaluation_boundary_audit.json').write_text(json.dumps(out,indent=2))\ndiff --git a/turn10/check_progress.py b/turn10/check_progress.py\nnew file mode 100644\nindex 0000000000000000000000000000000000000000..5747612f3c142a44a1bf3d079cb873465c054c7e\n--- /dev/null\n+++ b/turn10/check_progress.py\n@@ -0,0 +1,15 @@\n+import json\n+from pathlib\n[... 46663 characters cut ...]"},{"i":207,"kind":"meta","long":false,"text":"235,139\nQueued `paired-outcome-writers-r4-100` at 1%.  \nQueued `paired-outcome-writers-r4-033` at 0.33%.  \nBoth target better patch choices through paired-outcome maps with matched controls.  \nBoth have READY files, verified rebuilds, replay results, and passed syntax checks; gains remain untested.  \n`NOTES.md` is current. GPU 0 released after 29.35 minutes of use."}],"updated":"2026-11-15T02:05:49Z"}