Turn 11 · claude

# wsp31 author brief (read fully at the start of every turn)

You are one of three authors (claude, gpt, gemini) taking turns. Your job: make Gemma 4 31B solve more coding-agent
tasks **by editing its weights, with no training**. You read the model (weights, activations, traces, failures),
decide what to change, build the change as a closed-form edit, predict its effect, and queue it. A separate runner
spends the rollouts and writes the measured result next to your prediction. You are scored on tasks gained over the
champion in the same batch (the unedited model plus the edits that have already passed; see "The champion"), on the
margin over your matched control, and on how well your predictions held.

**Be bold.** Small safe nudges were tried on the 4B model and were lost in the noise (see `PRIOR_E4B.md`). You get
two entries per round and then wait for their results, so each one counts; a third variation of a null result is a
wasted round. High-risk ideas with a clear mechanism and a
prediction that could be wrong are what this programme wants. Say what would prove you wrong.

## Where you work

- Everything happens on host `wrx90`, reached with `ssh -o BatchMode=yes wrx90 '<command>'`. Write scripts in your
  local working directory, copy them with `scp`, run them with ssh. Keep ssh output small (`tail`, `cut`, `head`).
- Root: `/home/keith/gemma-v2` (below: `$R`). Python: `$R/tii-venv/bin/python` (torch, transformers, vLLM 0.19.1,
  peft, safetensors; no scipy). `. $R/env.sh` sets `R` and `PY`.
[... 206 lines cut ...]
- An edit that passes both stages is promoted: it becomes part of the champion for everything after it.
- The champion is confirmed on tasks you do not see, against the unedited model, and the final champion gets one
  pre-registered held-out run. A changed edit is a new edit.
- A combination of your own edits is a new queue entry with its own record, prediction and control. Combining with
  edits that already passed needs nothing from you: that is what the champion does.

Single-run agent evaluations are noisy by several tasks. An edit worth having shows up as ten or more tasks.
Aim there.

# Notes of author claude (rewritten end of turn 8, 14 Nov 2026, 1:42 AM ET)

## Scored so far
- 0008, 0020, 0021 (depth gate writing the end-of-thought state): harmful. Parked 0007, 0009, 0010,
  0022, 0023 are the same family: never resubmit.
- 0031 `icv-brief-b20`: +9.0 by the rule (77 against 72 and 64), waiting for stage 2. 0032 `icv-brief-b40`: +3.0 (71).
  x001 counters, unedited / dose 2 / dose 4: budget endings 45, 46 / 32 / 19; empty patch 21, 18 / 13 / 8;
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  Box batches have no request logs; `code/x_stats.py`, `x_seq.py`, `tr_look.py` read results and traces.

## Queued in turn 8
- 0038 `fcv-brief-b20`: paragraph I1 at dose 2 again, on the fourth-quietest neuron, self-consistent compile
  (`code/fcv_job.py`: hooked pass, a layer writes only what its shift still lacks). A replication of 0031 at about
  0.7 of its stream shift. Predicted -2 to 8.
- 0039 `fcv-brief-exact-b20`: the pair I1 + I5 ("be exact about what the issue asks ..."), same neurons, compile, dose
  (`code/fcv2_job.py`). Its difference to the sister in the same batch is I5's effect. Predicted -4 to 8;
  difference -5 to +6.
- If 0031 is promoted first, both stack on it to I1 at dose 4: expect null or harm; then queue I5 alone.

## Learned
[... 172 lines cut ...]
| 0027 | gpt | code-reader-damp-r4-033 | Damp the code-versus-prose style contrast in readers in all layers at 0.33 percent | parked | -8 to +14 |  |  | - |
| 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 |
| 0035 new | gpt | source-grounding-icv-b3 | Source-grounding instruction contrast across all 60 layers at dose 3 | done | -8 to +12 | -2.5 (79 vs 81) |  | null |
| 0036 new | gpt | source-grounding-icv-b1 | Source-grounding instruction contrast across all 60 layers at dose 1 | done | -8 to +10 | -3.5 (78 vs 81) |  | null |
| 0043 | gemini | spec-audit-thought-gate | Thought-gated reliability-shrunk Problem Statement spec-audit steering across all 60 MLP layers | running_s1 | +2 to +7 |  |  | - |
| 0044 | gemini | dual-audit-postedit-boost | Stateful two-neuron post-edit spec-audit boost with thought and edit-history gating over 180 MLP matrices | running_s1 | +3 to +8.5 |  |  | - |
| 0047 | gpt | paired-outcome-writers-r4-100 | Paired outcome writer map across all 60 layers at 1 percent | queued_s1 | -6 to +12 |  |  | - |
| 0048 | gpt | paired-outcome-writers-r4-033 | Paired outcome writer map across all 60 layers at 0.33 percent | queued_s1 | -4 to +9 |  |  | - |

# wsp31 queue status (2026-11-14 09:38:26 EST)

Rule: {"s1_promote": 3.0, "s1_harmful": -6.0, "s2_min": 4.0, "ctrl_margin": 5.0, "total_pass": 10.0, "total_harmful": -10.0}

Champion (the base every new edit is scored against): Generation 0: the unedited model. No edit has passed yet.

Reference arms of a new batch: the unedited model served through an all-zero adapter, the same serving path as an edit (ledger record 0033).

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## Batches

| batch | stage | gpu | state | arms | rows | note |
|---|---|---|---|---|---|---|
| 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]}} |
| b002-supp1 | s1 | 1 | done | base e0008 e0011 aa | 124 | {"tasks": 31, "record": "0041", "solved": {"base": [60, 73], "e0008": [51, 67], "e0011": [51, 65], "aa": [62, 77]}} |
| b008 | s2 | 0 | done | base e0031 c0031 aa | 872 | {"base": 114, "episodes": 218, "aa": [114, 111, 16, 13], "arms": {"e0031": [123, 10.5], "c0031": [119, 6.5]}} |
| x003 | s1 | box | done | base e0035 e0036 aa | 480 | {"base": 81, "episodes": 120, "aa": [81, 82, 3, 4], "arms": {"e0035": [79, -2.5], "e0036": [78, -3.5]}} |
| b004-supp1 | s1 | 1 | done | base e0021 e0020 aa | 76 | {"tasks": 19, "record": "0042", "solved": {"base": [56, 70], "e0021": [50, 60], "e0020": [47, 58], "aa": [59, 73]}} |
| b009 | s2 | 1 | done | base e0032 c0032 aa | 872 | {"base": 127, "episodes": 218, "aa": [127, 114, 20, 7], "arms": {"e0032": [123, 2.5], "c0032": [120, -0.5]}} |
[... 257 lines cut ...]
drwxrwxr-x  4 keith keith 4096 Nov 14 01:39 fcv-brief-b20
drwxrwxr-x  4 keith keith 4096 Nov 14 01:39 fcv-brief-exact-b20
drwxrwxr-x  4 keith keith 4096 Nov 13 19:51 icv-brief-b20
drwxrwxr-x  4 keith keith 4096 Nov 13 19:51 icv-brief-b40
drwxrwxr-x  4 keith keith 4096 Nov 13 01:08 net-deep-gate-close-b05
drwxrwxr-x  4 keith keith 4096 Nov 13 01:08 net-deep-gate-close-b12
drwxrwxr-x  4 keith keith 4096 Nov 13 01:08 net-preedit-commit-b12
drwxrwxr-x  4 keith keith 4096 Nov 13 01:08 net-preedit-commit-close-b05

 28053 tools/TOOLS.md
  9736 tools/ARCH.md
315339 interp/REPORT.md
353128 total
# wsp31 tools for edit authors

Changelog (newest first; times US Eastern):
- Fri 13 Nov, 3:51 PM: **three of the first four edits were harmful (-10 to -21 tasks): read "Before you submit"
  (section 5) first.** GPU 0 for pre-tests only while an author turn is open (section 3). New `delimprobe.py`.
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  12:39 AM speed (trap 12): **the server's rank limit sets the price of an adapter**.
- Thu 12 Nov: 11:40 PM first served runs of `dose.py`, `validate.py`, `vgen.py`, `closeprobe.py`; 10:55 PM stacks
  of rank 34 to 96 applied as written; 10:30 PM **thought-end pre-tests need exact contexts**, rank limits 64 or 128
  (never 96); 10:00 PM champion support, network-wide builders; 8:36 PM first version. Earlier commands all still work.

Everything here lives in `$R/wsp31/tools` (below `$T`; `$R = /home/keith/gemma-v2`). Each entry ends with
**Verified by** (a measurement that was made) or **NOT VERIFIED YET** (written, first real run still queued; use it,
but do not build a claim on its numbers alone). Architecture facts are in `$T/ARCH.md` (read "Consequences for
weight edits" there before designing an edit); measurements with commands are in `$T/REPORT.md`.

[... 222 lines cut ...]

The other probes use the labelled decision points of the default set (section 6; `--traces 12 --per-trace 8
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--alpha X`, `--project-out`. ACTIVE means only "moves the distribution": all four scored edits were ACTIVE, three
harmful. `dose.py` serves one edit at each whole-network size and
reports per dose the change at decision poi

Sat Nov 14 09:39:07 AM EST 2026
import json, sys, statistics as st, collections
B = "/home/keith/gemma-v2/results/wsp31/batches/x001/"
arms = {}
for a in ["base", "aa", "e0031", "e0032"]:
    rows = {}
    for l in open(B + a + "/rebench/shard0_gpu0/task_results.jsonl"):
        r = json.loads(l); rows[r["instance_id"]] = r
    arms[a] = rows
    errs = collections.Counter((r.get("agent_error") or "none")[:45] for r in rows.values())
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    tc = [r.get("tool_calls") or 0 for r in rows.values()]
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    sol = [r for r in rows.values() if r["resolved"]]
    tl = [r for r in rows.values() if "timeout" in (r.get("agent_error") or "")]
    print(a, "n", len(rows), "solved", len(sol), "| out tok med %.0f mean %.0f | at10k %d | calls med %.0f | capped calls mean %.2f | empty %d | timeout %d (solved among them %d) | tok/call med %.0f" % (
        st.median(ot), st.mean(ot), sum(o >= 9990 for o in ot), st.median(tc), st.mean(cap),
        sum(not r["patch_chars"] for r in rows.values()), len(tl), sum(r["resolved"] for r in tl),
        st.median([o / max(1, t) for o, t in zip(ot, tc)])))
    print("   ", dict(errs))
[... 90 lines cut ...]
| [0041](ledger/0041-claude-correction-b002-supp1.md) | 2026-11-14 | claude | edit | Correction of batch b002: 31 stage-1 task(s) run in their own images (b002-supp1) | wsp31_screen_v1, wsp31_screen_v2 / b002, b002-supp1 | done | n/a | corrected solved: base 60 to 73, e0008 51 to 67, e0011 51 to 65, aa 62 to 77 (of 120); verdict changes: none |
| [0042](ledger/0042-claude-correction-b004-supp1.md) | 2026-11-14 | claude | edit | Correction of batch b004: 19 stage-1 task(s) run in their own images (b004-supp1) | wsp31_screen_v1, wsp31_screen_v2 / b004, b004-supp1 | done | n/a | corrected solved: base 56 to 70, e0021 50 to 60, e0020 47 to 58, aa 59 to 73 (of 120); verdict changes: none |
| [0043](ledger/0043-gemini-spec-audit-thought-gate.md) | 2026-11-14 | gemini | edit | Thought-gated reliability-shrunk Problem Statement spec-audit steering across all 60 MLP layers | wsp31_screen_v2 / x006 | running | - | - |
| [0044](ledger/0044-gemini-dual-audit-postedit-boost.md) | 2026-11-14 | gemini | edit | Stateful two-neuron post-edit spec-audit boost with thought and edit-history gating over 180 MLP matrices | wsp31_screen_v2 / x006 | running | - | - |
| [0045](ledger/0045-claude-correction-b008-supp1.md) | 2026-11-14 | claude | edit | Correction of batch b008: 2 stage-2 task(s) run in their own images (b008-supp1) | wsp31_screen_v2 / b008, b008-supp1 | done | n/a | corrected solved: base 114 to 113, e0031 123 to 122, c0031 119 to 120, aa 111 to 112 (of 218); verdict changes: none |
| [0046](ledger/0046-claude-correction-b009-supp1.md) | 2026-11-14 | claude | edit | Correction of batch b009: 2 stage-2 task(s) run in their own images (b009-supp1) | wsp31_screen_v2 / b009, b009-supp1 | done | n/a | corrected solved: base 127 to 127, e0032 123 to 123, c0032 120 to 120, aa 114 to 114 (of 218); verdict changes: none |
| [0047](ledger/0047-gpt-paired-outcome-writers-r4-100.md) | 2026-11-14 | gpt | edit | Paired outcome writer map across all 60 layers at 1 percent | wsp31_screen_v2 / b010 | running | - | - |
| [0048](ledger/0048-gpt-paired-outcome-writers-r4-033.md) | 2026-11-14 | gpt | edit | Paired outcome writer map across all 60 layers at 0.33 percent | wsp31_screen_v2 / b010 | running | - | - |

base n 120 solved 78 | out tok med 9990 mean 10470 | at10k 60 | calls med 22 | capped calls mean 2.83 | empty 7 | timeout 18 (solved among them 4) | tok/call med 373
    {'none': 102, 'Agent exceeded session timeout (7.5 min)': 18}
    {'patch_done_fail': 27, 'solved': 78, 'patch_timeout_fail': 8, 'empty': 7}
aa n 120 solved 76 | out tok med 9021 mean 10359 | at10k 48 | calls med 21 | capped calls mean 2.82 | empty 8 | timeout 21 (solved among them 5) | tok/call med 392
    {'none': 99, 'Agent exceeded session timeout (7.5 min)': 21}
    {'patch_done_fail': 28, 'solved': 76, 'empty': 8, 'patch_timeout_fail': 8}
e0038 n 120 solved 75 | out tok med 6425 mean 8652 | at10k 42 | calls med 19 | capped calls mean 1.82 | empty 5 | timeout 11 (solved among them 1) | tok/call med 313
    {'none': 109, 'Agent exceeded session timeout (7.5 min)': 11}
    {'patch_done_fail': 34, 'solved': 75, 'empty': 5, 'patch_timeout_fail': 6}
e0039 n 120 solved 79 | out tok med 6838 mean 8667 | at10k 41 | calls med 19 | capped calls mean 1.95 | empty 3 | timeout 15 (solved among them 1) | tok/call med 328
    {'none': 105, 'Agent exceeded session timeout (7.5 min)': 15}
    {'patch_done_fail': 27, 'solved': 79, 'empty': 3, 'patch_timeout_fail': 11}
{"agent_seconds": 689.77, "budget": 20000, "calls": 37, "capped_calls": 18, "no_limit_calls": 3, "uncounted_calls": 0, "wall_limit_hit": false}
e0038 gained over both:
    [task] [('base', 7108, 16, 1756, ''), ('aa', 6140, 13, 1765, ''), ('e0038', 10469, 25, 1578, '')]
    [task] [('base', 13054, 35, 2411, ''), ('aa', 20000, 42, 2463, 'Agent exceed'), ('e0038', 5748, 23, 1415, '')]
e0038 lost vs both:
    django-money__django-money.835c1ab8.combine_module__bqggrnha [('base', 8713, 26, 1350, ''), ('aa', 9144, 18, 1350, ''), ('e0038', 16014, 25, 1308, '')]
    jsvine__pdfplumber.02ff4313.func_pm_remove_assign__1v9soh1j [('base', 6248, 22, 480, ''), ('aa', 5189, 21, 480, ''), ('e0038', 12532, 42, 923, '')]
    mozilla__bleach.73871d76.func_pm_remove_cond__dfyej8pm [('base', 10005, 36, 1501, ''), ('aa', 9431, 27, 761, ''), ('e0038', 20000, 59, 957, 'Agent exceed')]
[... 5 lines cut ...]
    [task] [('base', 7108, 16, 1756, ''), ('aa', 6140, 13, 1765, ''), ('e0039', 8905, 17, 1174, '')]
    [task] [('base', 13054, 35, 2411, ''), ('aa', 20000, 42, 2463, 'Agent exceed'), ('e0039', 10795, 49, 1255, '')]
e0039 lost vs both:
    pallets__markupsafe.620c06c9.combine_file__7pv2r8sa [('base', 10778, 20, 941, ''), ('aa', 9316, 19, 944, ''), ('e0039', 6129, 20, 768, '')]
    prettytable__prettytable.ca90b055.combine_file__2mwa4qpg [('base', 6161, 16, 1068, ''), ('aa', 5778, 15, 1068, ''), ('e0039', 5136, 17, 1095, '')]
    [task] [('base', 15103, 25, 1009, ''), ('aa', 13932, 35, 1363, ''), ('e0039', 15229, 25, 670, '')]
    [task] [('base', 4253, 16, 1153, ''), ('aa', 9493, 43, 1811, ''), ('e0039', 5930, 32, 1874, '')]
    rubik__radon.54b88e58.func_basic__8pbqxg0r [('base', 15883, 19, 1373, ''), ('aa', 16469, 21, 1447, ''), ('e0039', 20000, 26, 1516, 'Agent exceed')]

Sat Nov 14 09:40:21 AM EST 2026
"""fcv_job.py (author claude, turn 8): one GPU-0 hold with tools/g31.py (forward pass only, no server).

Self-consistent ("faithful") compile of the instruction paragraph I1 of code/icv_job.py into one always-on MLP neuron
per layer. Turn 6 (entries icv-brief-b20 / b40) wrote delta_L = d_L - layer_scalar_L * d_{L-1}: that assumes a layer
passes a shift of its input through unchanged. Layers respond to a shifted input, so the served edit moved the stream
about twice as far as the paragraph, at a cosine of 0.4 to 0.5. Here the write of layer L is what is still missing
once every earlier layer already carries the paragraph's mean shift:
  one pass per call and dose beta with a hook after every layer L (on resid_post, all positions but BOS):
      s_L = mean over the completion positions P of (resid_post_L of this pass - resid_post_L of the unedited pass)
      c_L = beta * d_L - s_L ;  resid_post_L += c_L      (so the mean shift over P is beta * d_L after every layer)
  F_L[beta] = mean over calls of c_L.  d_L is the paragraph's mean shift measured in turn 6 on the same calls
  (code/data/icv_stats.pt). The always-on neuron (fourth-quietest neuron of the layer, not the third as in turn 6,
  so that this edit and icv-brief-b20 can be stacked) writes F_L[beta].
Then the turn-6 teacher-forced evaluation on the held-out calls: base, prompted with I1, each arm.
`--mock` runs the plumbing on CPU with random numbers.
"""
import json
import os
import random
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scratch/job9:
ad
close_G20.json
eval.pt
fcv2_stats.pt
gen.json
gen_arms.txt
summary.json

#### 0043-gemini-spec-audit-thought-gate.md
## Hypothesis

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2. Unconditional brevity steering (`0038 fcv-brief-b20`) turned negative (`-2.0` on `safe_s1`) under `x2` because truncating thoughts rushed verification and increased `wrong_clean` from `23.5` to `31` (`+7.5` wrong patches), whereas adding exactness (`0039 fcv-brief-exact-b20`, `+2.0`) recovered `+4.0` tasks over `0038` despite `94%` of its vector still coming from `"think briefly"` and unshrunk `fcv` subtraction injecting negative split-half noise (`-0.15` to `-0.26`) in upper layers `L36..59`.
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We hypothesize that replacing 1 near-dead MLP neuron per layer (`0..59`, 180 matrices) with (a) a **non-negative quadratic GeGLU thought-only gate** (`up_row = gate_row / 3.0`, strictly `>= 0` everywhere, active inside `<|channel>thought` and `150x` suppressed on BOS, prompt, `<|"|>` delimiters, and JSON tool arguments) and (b) a **Gemma-4 `layer_scalar`-exact, Spearman-Brown reliability-shrunk incremental stream write** distilled purely from an adversarial Problem Statement spec-and-edge-case audit paragraph (`P_audit`, zero `"think briefly"` text) will steer global-attention queries back to the Problem Statement and elicit targeted `python3 -c` boundary checks before `submit_patch` without breaking tool-call syntax.

## Exact recipe

base: champion generation 0
size: whole network 0.9960% over 180 matrices, largest matrix 12.7118%
control size: whole network 0.9961% over 180 matrices, largest matrix 12.7124%

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- **Stage-1 safe data hygiene (zero Stage-2 or sealed-set contact)**: All fitting and pre-testing use only `safe_s1 = (stage1_ids & stage1_ids_v2) - (stage2_ids | stage2_ids_v2 | stage2_ids_240)` (`104` tasks; `78` fit pool, `26` unseen held-out pool), using unedited `x003/base` request logs with zero outcome (`resolved`) labels.
- Pre-edit fit calls (16): [task]#c5(read_file), Mimino666__langdetect.a1598f1a.lm_rewrite__dk9wx21q#c5(read_file), [task]#c22(run_command), [task]#c5(run_command), [task]#c31(run_command), gweis__isodate.17cb25eb.func_basic__ydtogylj#c4(run_command), [task]#c17(read_file), [task]#c10(run_command), pallets__markupsafe.620c06c9.func_basic__fpb7w0tc#c3(read_file), [task]#c4(read_file), [task]#c11(read_file), [task]#c4(read_file), lepture__mistune.bf54ef67.combine_module__dalnbilu#c3(read_file), prettytable__prettytable.ca90b055.func_basic__1mmuxqev#c5(run_command), kurtmckee__feedparser.cad965a3.pr_469#c3(read_file), [task]#c4(read_file)
[... 101 lines cut ...]
| cpu100_edit | 25/1073 | -0.00044 | -0.01753 | 112 | 0 | NOT BROKEN |
| cpu100_ctrl | 28/1073 | -0.01563 | -0.03913 | 111 | 2 | NOT BROKEN |

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These checks can exclude a large local syntax break; they do not test full-episode looping, total tool use or patch correctness. The reference's after-close panel contains only three edit_file calls; most are reads or shell commands, so code-writing coverage is thin. The dose choice uses these panels, so they are development checks. The custom transport capture/scout code is new; g31 and the official replay backend are documented as verified, but the transport-to-solve-rate link is unvalidated.

Sat Nov 14 09:43:05 AM EST 2026
"""fcv2_build.py OUT_DIR G10|G20 edit|ctrl  (author claude, turn 8; CPU, seconds)

Rebuilds one arm of code/fcv2_job.py bit for bit from the statistics that job saved (code/data/fcv2_stats.pt: the
self-consistent per-layer writes G_L[beta] of the paragraph pair I1 + I5, the always-on neuron of every layer, the MLP output RMS, the norm weights
and layer scalars). edit: the down column of the always-on neuron of layer L writes G_L[beta]. ctrl: the same code
path with the sign of every coordinate of the written vector flipped at random (seed 6000 + L): identical neurons,
identical gate and up rows, identical per-coordinate magnitudes of the write, so identical |dW|_F.
"""
import sys

import torch

A_DIR = "/home/keith/gemma-v2/wsp31/authors/claude"
sys.path.insert(0, A_DIR + "/code")
import fcv2_job as F  # noqa: E402

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assert kind in ("edit", "ctrl")
st = torch.load(A_DIR + "/code/data/fcv2_stats.pt")
[... 146 lines cut ...]
45:`self_attn.k_norm.weight` (each [head_dim], shared by all heads of the layer), `layer_scalar` [1]. The vision tower
62:x  = norm_pre_feedforward(h)                              [mlp_in]      what gate_proj / up_proj rows read
63:g  = gate_proj x                                          [gate]
65:n  = gelu_tanh(g) * u                                     [mlp_act]     neuron activations, 21504 per position
67:mo = norm_post_feedforward(y)                             [mlp_out]
68:h  = (h + mo) * layer_scalar                              [resid_post]
77:`layer_scalar` multiplies the whole stream, skip path included. Values: layer 0 0.099, layer 1 0.073, layers 2-22
94:3. **Reads see the normalised stream.** `gate_proj`, `up_proj`, `q_proj`, `k_proj`, `v_proj` rows read

def log(*a):
    print(f"[{time.time() - T0:7.1f}]", *a, flush=True)


def pick(recs):
    s1 = set(open(SETS + "/stage1_ids.txt").read().split())
    s2 = set(open(SETS + "/stage2_ids.txt").read().split()) | set(open(SETS + "/stage2_ids_v2.txt").read().split())
    by = {}
    for r in recs:
        if r["instance"] not in s1 or r["instance"] in s2 or "/batches/b001/" not in r["run"]:
            continue
        c = r["calls"][-1]
        if r["n"] > NMAX or len(c["comp"]) < 24 or 101 not in c["comp"] or c["comp"][0] != 100 or r["call"] < 1:
            continue
        if c["start"] + len(c["comp"]) != r["n"]:
            continue
        by.setdefault(r["instance"], []).append(r)
    inst = sorted(by)
    train, ev = [], []
    for i, x in enumerate(inst):
[... 379 lines cut ...]
    json.dump(sm, open(S + "/summary.json", "w"), indent=1)
    for k, v in sm.items():
        log("SUMMARY", k, json.dumps(v))
    log("done")


if __name__ == "__main__":
    main()

Sat Nov 14 09:44:31 AM EST 2026
               total        used        free      shared  buff/cache   available
Mem:             183          17          87           0          81         166
276:    def forward(self, ids, out_pos=None, capture=None, cap_layers=None, cap_pos=None, hooks=None, stop_after=None,
277-                topk=None):
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279-
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282-        capture: iterable of names from CAPS, taken at cap_pos (default out_pos) for cap_layers (default all):
283-          resid_pre (layer input), attn_out (attention write after its post-norm), resid_mid, mlp_in (MLP input after
284-          the pre-feedforward norm: what gate_proj/up_proj rows read), gate, up (pre-activations), mlp_act
285-          (gelu_tanh(gate) * up: the neuron activations that down_proj columns write), mlp_raw (down_proj output),
286-          mlp_out (MLP write after its post-norm), resid_post (layer output after layer_scalar).
287-        hooks: {(name, layer): fn(tensor [N, dim]) -> tensor} applied to the full-sequence tensor at that point.
288-        stop_after: stop after this layer index (no log-probs returned).
289-        Returns dict(logprobs fp32 [len(out_pos), vocab] or (values, indices) if topk, caps {name: fp32 cpu
290-        [n_cap_layers, len(cap_pos), dim]}).
291-        """
292-        a = self.arch
[... 92 lines cut ...]
142-        o, i = self._check(l, mod)
143-        assert 0 <= j < o
144-        d = torch.as_tensor(delta, dtype=torch.float32).reshape(i)
bash: line 1: /tii-venv/bin/python: No such file or directory
0, 2 MiB, 97887 MiB
1, 90682 MiB, 97887 MiB
/home/keith/gemma-v2/wsp31/gpu0.lock
claude 1794667092

23:T0 = time.time()
29:from edits import EditSet  # noqa: E402
40:DEADLINE_CAPTURE, DEADLINE = 400, 860
111:        if time.time() - T0 > DEADLINE_CAPTURE:
238:    e = EditSet()
286:        if time.time() - T0 > DEADLINE - 40:
301:            if time.time() - T0 > DEADLINE:
421:    global DEADLINE, DEADLINE_CAPTURE
428:        DEADLINE = min(DEADLINE, TURN_END - 27 * 60 - T0)
429:        DEADLINE_CAPTURE = min(DEADLINE_CAPTURE, 0.47 * DEADLINE)
Sat Nov 14 09:47:20 AM EST 2026
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[   19.1] solved 5 lam 3.0 held-out R2 rank8 -0.001 full -0.002 const 0.001 | fit R2 0.841 energy 0.997 | use False
[   19.1] solved 30 lam 0.3 held-out R2 rank8 0.011 full 0.009 const 0.004 | fit R2 0.562 energy 0.751 | use False
[   19.1] solved 59 lam 3.0 held-out R2 rank8 -0.030 full -0.038 const -0.016 | fit R2 0.084 energy 0.546 | use False
[   19.1] layers used []
[   19.1] held-out R2 (rank 8) by layer ['5:-0.00', '30:0.01', '59:-0.03']
[   19.1] const R2 by layer ['5:0.00', '30:0.00', '59:-0.02']
[... 11 lines cut ...]

[   19.1] arms ['H23']
[   29.2] evaluated 0 gawel__pyquery.811cd048.lm_rewri call 2 pos 268 variants 3
[   29.2] SUMMARY P_I15 {"records": 1, "positions": 268, "flip_all": 0.033582089552238806, "flip_thought": 0.032388663967611336, "n_thought": 247, "early_close_top": 0, "dlogp_close_inside": 0.008113112044237886, "n_close": 1, "dlogp_close_at_close": -2.0565638542175293, "close_kept": 0, "n_tool": 1, "flip_tool": 0, "kl_base": 0.01419271817847864, "tv_base": 0.023710606703117712, "dlogp_logged": -0.021455456961446732}
[   29.2] SUMMARY H23 {"records": 1, "positions": 268, "flip_all": 0.022388059701492536, "flip_thought": 0.020242914979757085, "n_thought": 247, "early_close_top": 0, "dlogp_close_inside": -0.2302008099884157, "n_close": 1, "dlogp_close_at_close": -0.5306169986724854, "close_kept": 0, "n_tool": 1, "flip_tool": 0, "kl_base": 0.008462741303799757, "tv_base": 0.02056868930361164, "dlogp_logged": -0.005974913710978494, "kl_prompt_to_arm": 0.007384455470896479, "kl_prompt_to_base": 0.01419271817847864, "reproduced": 0.479701113061343, "shift_cos": 0.38078086055926424, "prompt_flips": 9, "prompt_flips_matched": 4, "resid_cos": ["0.80", "0.61", "0.35", "0.39", "0.24", "0.46", "0.64", "0.58", "0.56", "0.47", "0.39"], "resid_ratio": ["0.41", "1.59", "4.43", "5.06", "2.90", "1.70", "1.30", "1.28", "1.31", "1.38", "1.38"]}
[   29.2] SUMMARY neuron_act_over_gbar {"layers": [0, 6, 12, 18, 24, 30, 36, 42, 48, 54, 59], "bos": ["0.96", "0.56", "2.06", "3.31", "1.49", "0.63", "0.48", "0.82", "0.86", "0.54", "0.25"], "prompt_mean": ["0.90", "0.83", "0.80", "0.93", "0.93", "0.84", "0.76", "0.88", "0.90", "0.87", "0.88"], "prompt_sd": ["0.08", "0.14", "0.11", "0.12", "0.07", "0.13", "0.17", "0.14", "0.12", "0.13", "0.18"], "prompt_max": ["1.05", "1.18", "1.04", "1.11", "1.09", "1.11", "1.11", "1.11", "1.14", "1.19", "1.16"], "comp_mean": ["0.96", "0.97", "0.95", "0.98", "0.94", "0.83", "0.87", "0.91", "0.94", "0.96", "0.99"], "comp_sd": ["0.08", "0.10", "0.11", "0.11", "0.07", "0.12", "0.12", "0.10", "0.09", "0.08", "0.07"], "comp_min": ["0.67", "0.67", "0.62", "0.68", "0.74", "0.55", "0.61", "0.68", "0.53", "0.70", "0.77"], "comp_max": ["1.24", "1.35", "1.21", "1.26", "1.10", "1.13", "1.15", "1.23", "1.20", "1.25"
[   29.2] done
Sat Nov 14 09:47:50 AM EST 2026

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Placeholders: {{COMPILE}} (per-layer facts of the self-consistent write), {{PRETEST}} (teacher-forced table),
{{STREAM}} (stream shift against the prompted shift), {{NEURON}}, {{GEN}} (served single turns), {{CLOSE}},
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Then checks the record with the runner's parser.
"""
import json
import os
import sys

import torch

A = "/home/keith/gemma-v2/wsp31/authors/claude"
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job = sys.argv[4] if len(sys.argv) > 4 else "job8"
S = A + "/scratch/" + job
st = torch.load(A + "/code/data/" + ("fcv2_stats.pt" if job == "job9" else "fcv_stats.pt"))
sm = json.load(open(S + "/summary.json"))
LBL = {"P_I1": "prompted with the paragraph (the target)", "F10": "self-consistent compile, dose 1 (F10)", "F20": "self-consistent compile, dose 2 (F20)",
[... 136 lines cut ...]
cd /home/keith/gemma-v2/wsp31/authors/claude
export WSP31_WORK=$PWD/scratch CUDA_DEVICE_ORDER=PCI_BUS_ID CUDA_VISIBLE_DEVICES=0
date > scratch/hold11_start
[ $(date +%s) -gt $(date -d "2026-11-14 01:42:00" +%s) ] && { echo late > scratch/hold11_end; exit 0; }
timeout 230 $PY $R/wsp31/tools/closeprobe.py --adapter $PWD/scratch/job8/ad/F20 --out $PWD/scratch/job8/close_F20.json > scratch/logs/close8_F20.log 2>&1
date > scratch/hold11_end
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Sat Nov 14 09:55:08 AM EST 2026
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[  382.9] layers used [1, 2, 6, 9, 17, 23, 26, 29, 30, 35, 39, 41, 47, 53]
[  382.9] held-out R2 (rank 8) by layer ['0:-0.40', '1:0.16', '2:0.18', '3:-0.24', '4:-0.71', '5:0.02', '6:0.46', '7:-0.09', '8:-0.25', '9:0.07', '10:0.04', '11:0.04', '12:-0.03', '13:-1.36', '14:-4.89', '15:-9.92', '16:-4.09', '17:0.12', '18:-0.08', '19:-0.24', '20:-0.98', '21:-0.17', '22:-0.79', '23:0.13', '24:-0.62', '25:-0.03', '26:0.36', '27:-0.42', '28:-0.03', '29:0.36', '30:0.12', '31:0.04', '32:0.02', '33:-0.12', '34:0.01', '35:0.40', '36:-0.00', '37:0.03', '38:0.02', '39:0.07', '40:0.02', '41:0.39', '42:0.00', '43:0.01', '44:0.01', '45:0.01', '46:0.03', '47:0.14', '48:0.01', '49:0.02', '50:0.00', '51:0.04', '52:0.00', '53:0.08', '54:0.00', '55:0.01', '56:-0.00', '57:0.02', '58:0.03', '59:0.01']
[  382.9] const R2 by layer ['0:0.02', '1:0.02', '2:0.01', '3:0.00', '4:0.02', '5:0.01', '6:0.01', '7:0.01', '8:0.00', '9:0.00', '10:-0.00', '11:0.02', '12:-0.00', '13:0.00', '14:-0.00', '15:-0.00', '16:-0.00', '17:0.00', '18:0.00', '19:-0.00', '20:-0.00', '21:0.00', '22:0.00', '23:0.01', '24:0.00', '25:0.00', '26:0.00', '27:-0.00', '28:-0.00', '29:0.02', '30:0.00', '31:0.00', '32:0.00', '33:0.00', '34:0.00', '35:0.01', '36:0.00', '37:0.00', '38:0.00', '39:0.00', '40:0.00', '41:0.01', '42:0.00', '43:0.01', '44:0.01', '45:0.01', '46:0.01', '47:0.02', '48:0.01', '49:0.01', '50:0.01', '51:0.01', '52:0.01', '53:0.01', '54:0.00', '55:0.01', '56:0.01', '57:0.01', '58:0.01', '59:0.00']
[  382.9] built M10 r 8 net_rel 0.00428
[  382.9] built M10c r 8 net_rel 0.00428
[  382.9] built M20 r 8 net_rel 0.00857
[  382.9] built M20c r 8 net_rel 0.00857
[  382.9] arms ['H23', 'M10', 'M20', 'M10c', 'H23c', 'G20', 'M20c']
[  382.9] arms ['H23', 'M10', 'M20', 'M10c', 'H23c', 'G20', 'M20c']
[  412.7] evaluated 0 gawel__pyquery.811cd048.lm_rewri call 2 pos 268 variants 9

Sat Nov 14 09:59:25 AM EST 2026
[  645.1] SUMMARY P_I15 {"records": 8, "positions": 1278, "flip_all": 0.018779342723004695, "flip_thought": 0.03695652173913044, "n_thought": 460, "early_close_top": 0, "dlogp_close_inside": -0.0060778058093527085, "n_close": 8, "dlogp_close_at_close": -0.20197624185379937, "close_kept": 7, "n_tool": 8, "flip_tool": 0, "kl_base": 0.007701813848179084, "tv_base": 0.014357204588366226, "dlogp_logged": -0.0061283537925618916}
[  645.1] SUMMARY H23 {"records": 8, "positions": 1278, "flip_all": 0.01643192488262911, "flip_thought": 0.02826086956521739, "n_thought": 460, "early_close_top": 0, "dlogp_close_inside": -0.21315376032953676, "n_close": 8, "dlogp_close_at_close": -0.06723532910200447, "close_kept": 7, "n_tool": 8, "flip_tool": 0, "kl_base": 0.006593567699613705, "tv_base": 0.014434776488977232, "dlogp_logged": -0.0032762517403455596, "kl_prompt_to_arm": 0.0048240249472231555, "kl_prompt_to_base": 0.007701813848179084, "reproduced": 0.3736507993680366, "shift_cos": 0.3753778848662996, "prompt_flips": 24, "prompt_flips_matched": 13, "resid_cos": ["0.23", "0.71", "0.45", "0.48", "0.30", "0.45", "0.58", "0.49", "0.50", "0.46", "0.43"], "resid_ratio": ["4.98", "1.93", "5.00", "7.04", "3.20", "1.80", "1.59", "1.37", "1.36", "1.24", "1.25"]}
[  645.1] SUMMARY M10 {"records": 8, "positions": 1278, "flip_all": 0.009389671361502348, "flip_thought": 0.015217391304347827, "n_thought": 460, "early_close_top": 0, "dlogp_close_inside": -0.025898434286532195, "n_close": 8, "dlogp_close_at_close": -0.008652829646962346, "close_kept": 7, "n_tool": 8, "flip_tool": 0, "kl_base": 0.002466179908534544, "tv_base": 0.007895874888497712, "dlogp_logged": -0.00018309316188330196, "kl_prompt_to_arm": 0.005433329248419017, "kl_prompt_to_base": 0.007701813848179084, "reproduced": 0.2945390065869221, "shift_cos": 0.3666179385356873, "prompt_flips": 24, "prompt_flips_matched": 7, "resid_cos": ["0.00", "0.10", "0.16", "0.29", "0.27", "0.49", "0.51", "0.45", "0.47", "0.43", "0.48"], "resid_ratio": ["0.00", "4.90", "3.71", "2.31", "0.92", "0.82", "0.73", "0.76", "0.81", "0.82", "0.73"]}
[  645.1] SUMMARY M20 {"records": 8, "positions": 1278, "flip_all": 0.01486697965571205, "flip_thought": 0.02826086956521739, "n_thought": 460, "early_close_top": 0, "dlogp_close_inside": 0.012591791152954102, "n_close": 8, "dlogp_close_at_close": -0.16488948475625875, "close_kept": 7, "n_tool": 8, "flip_tool": 0, "kl_base": 0.008642622982392288, "tv_base": 0.014957715717839524, "dlogp_logged": -0.006349329389223657, "kl_prompt_to_arm": 0.005363077409157357, "kl_prompt_to_base": 0.007701813848179084, "reproduced": 0.3036604733798737, "shift_cos": 0.4308585165438704, "prompt_flips": 24, "prompt_flips_matched": 13, "resid_cos": ["0.00", "0.13", "0.28", "0.39", "0.33", "0.51", "0.62", "0.53", "0.53", "0.52", "0.59"], "resid_ratio": ["0.00", "7.68", "7.00", "5.52", "2.18", "1.39", "1.17", "1.13", "1.17", "1.14", "1.08"]}
[  645.1] SUMMARY M10c {"records": 8, "positions": 1278, "flip_all": 0.007042253521126761, "flip_thought": 0.015217391304347827, "n_thought": 460, "early_close_top": 0, "dlogp_close_inside": 0.05095340687295665, "n_close": 8, "dlogp_close_at_close": -0.050039432898756786, "close_kept": 7, "n_tool": 8, "flip_tool": 0, "kl_base": 0.0008990683640952401, "tv_base": 0.004954842334621949, "dlogp_logged": -0.00047687535846084123, "kl_prompt_to_arm": 0.008309694724113728, "kl_prompt_to_base": 0.007701813848179084, "reproduced": -0.07892697589391418, "shift_cos": 0.22503707330551506, "prompt_flips": 24, "prompt_flips_matched": 4, "resid_cos": ["0.00", "0.09", "0.14", "0.23", "0.15", "0.24", "0.27", "0.28", "0.33", "0.32", "0.31"], "resid_ratio": ["0.00", "4.87", "3.68", "2.26", "0.96", "0.74", "0.64", "0.69", "0.73", "0.76", "0.66"]}
[  645.1] SUMMARY H23c {"records": 8, "positions": 1278, "flip_all": 0.010954616588419406, "flip_thought": 0.015217391304347827, "n_thought": 460, "early_close_top": 0, "dlogp_close_inside": -0.0897188471711200
[... 2339 characters cut ...]

def close_txt():
    L = []
    for k in ["F10", "F20", "F30"]:
        p = A + "/scratch/logs/close8_%s.log" % k
        if os.path.exists(p):
            t = [l.strip() for l in open(p) if l.startswith("change of log p(close)")]
            if t:
                L.append("- %s: %s" % (LBL[k], "; ".join(t)))
    return "\n".join(L) if L else "- not run this turn (no time left in the second hold); the only numbers are the 8 closes of the table above."


def size_txt(k):
            t = [l.strip() for l in open(p) if l.startswith("change of log p(close)")]
            if t:
                L.append("- %s: %s" % (LBL[k], "; ".join(t)))
    return "\n".join(L) if L else "- not run this turn (no time left in the second hold); the only numbers are the 8 closes of the table above."


def size_txt(k):
    d = json.load(open(A + "/scratch/size_%s.json" % slug))[k]["summary"]
[... 21 lines cut ...]
close_G20.json
eval.pt
fcv2_stats.pt
gen.json
gen_arms.txt
summary.json
{'probeset': '/home/keith/gemma-v2/wsp31/tools/data/probe_calls_b001_full.jsonl', 'records': 40, 'points': 166, 'champion': None, 'adapter': '/home/keith/gemma-v2/wsp31/authors/claude/scratch/job9/ad/G20', 'episodes': 40, 'reference': {'close': {'all': {'n': 40, 'logp_close': -0.07054737955331802, 'top_is_close': 1.0, 'logp_logged': -0.07054738700389862, 'top_is_logged': 1.0}, 'depth<200': {'n': 33, 'logp_close': -0.06415323168039322, 'top_is_close': 1.0, 'logp_logged': -0.06415323913097382, 'top_is_logged': 1.0}, '200..799': {'n': 6, 'logp_close': -0.10951236635446548, 'top_is_close': 1.0, 'logp_logged': -0.10951236635446548, 'top_is_logged': 1.0}, '800+': {'n': 1, 'logp_close': -0.04776439443230629, 'top_is_close': 1.0, 'logp_logged': -0.04776439443230629, 'top_is_logged': 1.0}}, 'cont': {'all': {'n': 126, 'logp_close': -19.571943283081055, 'top_is_close': 0.0, 'logp_logged': -0.11390814930200577, 'top_is_logged': 0.9920634627342224}, 'depth<200': {'n': 112, 'logp_close': -19.710859298706055, 'top_is_close': 0.0, 'logp_logged': -0.10991353541612625, 'top_is_logged': 0.9910714030265808}, '200..799': {'n': 13, 'logp_close': -19.207509994506836, 'top_is_close': 0.0, 'logp_logged': -0.15702924132347107, 'top_is_logged': 1.0}, '800+': {'n': 1, 'logp_close': -8.75072956085205, 'top_is_close': 0.0, 'logp_logged': -0.0007297713309526443, 'top_is_logged': 1.0}}}, 'base_s': 0.1, 'edit': {'close': {'all': {'n': 40, 'logp_close': -0.036193590611219406, 'top_is_close': 1.0, 'logp_logged
[    3.4] arms ['Q10', 'Q20', 'Q30', 'Q20c']

Sat Nov 14 10:02:03 AM EST 2026
1 {'lam': 3.0, 'r2': 0.163, 'r2_full': 0.165, 'r2_const': 0.019, 'energy': 0.938, 'fit_r2': 0.328, 'ynorm': 24.695, 'pnorm': 12.038, 'use': True, 'n': 5817}
2 {'lam': 3.0, 'r2': 0.175, 'r2_full': 0.175, 'r2_const': 0.007, 'energy': 0.967, 'fit_r2': 0.356, 'ynorm': 2.554, 'pnorm': 1.373, 'use': True, 'n': 5817}
6 {'lam': 3.0, 'r2': 0.457, 'r2_full': 0.458, 'r2_const': 0.006, 'energy': 0.994, 'fit_r2': 0.586, 'ynorm': 6.013, 'pnorm': 3.593, 'use': True, 'n': 5817}
9 {'lam': 3.0, 'r2': 0.074, 'r2_full': 0.072, 'r2_const': 0.001, 'energy': 0.956, 'fit_r2': 0.354, 'ynorm': 1.79, 'pnorm': 0.691, 'use': True, 'n': 5817}
17 {'lam': 3.0, 'r2': 0.119, 'r2_full': 0.118, 'r2_const': 0.004, 'energy': 0.953, 'fit_r2': 0.276, 'ynorm': 5.059, 'pnorm': 1.363, 'use': True, 'n': 5817}
23 {'lam': 3.0, 'r2': 0.128, 'r2_full': 0.135, 'r2_const': 0.012, 'energy': 0.849, 'fit_r2': 0.281, 'ynorm': 0.578, 'pnorm': 0.177, 'use': True, 'n': 5817}
26 {'lam': 0.03, 'r2': 0.357, 'r2_full': 0.329, 'r2_const': 0.001, 'energy': 0.809, 'fit_r2': 0.771, 'ynorm': 0.238, 'pnorm': 0.089, 'use': True, 'n': 5817}
29 {'lam': 3.0, 'r2': 0.361, 'r2_full': 0.415, 'r2_const': 0.021, 'energy': 0.907, 'fit_r2': 0.548, 'ynorm': 0.23, 'pnorm': 0.108, 'use': True, 'n': 5817}
30 {'lam': 0.3, 'r2': 0.116, 'r2_full': 0.07, 'r2_const': 0.002, 'energy': 0.667, 'fit_r2': 0.424, 'ynorm': 0.216, 'pnorm': 0.085, 'use': True, 'n': 5817}
35 {'lam': 0.3, 'r2': 0.399, 'r2_full': 0.417, 'r2_const': 0.013, 'energy': 0.772, 'fit_r2': 0.567, 'ynorm': 0.428, 'pnorm': 0.17, 'use': True, 'n': 5817}
39 {'lam': 0.3, 'r2': 0.072, 'r2_full': -0.036, 'r2_const': 0.002, 'energy': 0.38, 'fit_r2': 0.215, 'ynorm': 0.134, 'pnorm': 0.043, 'use': True, 'n': 5817}
41 {'lam': 0.3, 'r2': 0.393, 'r2_full': 0.351, 'r2_const': 0.009, 'energy': 0.723, 'fit_r2': 0.478, 'ynorm': 0.351, 'pnorm': 0.13, 'use': True, 'n': 5817}
47 {'lam': 0.3, 'r2': 0.143, 'r2_full': 0.084, 'r2_const': 0.015, 'energy': 0.5, 'fit_r2': 0.17, 'ynorm': 0.654, 'pnorm': 0.176, 'use': True, 'n': 5817}
53 {'lam': 3.0, 'r2': 0.081, 'r2_full': 0.075, 'r2_const': 0.015, 'energy': 0.712, 'fit_r2': 0.098, 'ynorm': 0.611, 'pnorm': 0.156, 'use': True, 'n': 5817}
5 {'lam': 3.0, 'r2': 0.021, 'r2_full': 0.022, 'r2_const': 0.006, 'energy': 0.925, 'fit_r2': 0.237, 'ynorm': 5.756, 'pnorm': 1.902, 'use': False, 'n': 5817}
11 {'lam': 3.0, 'r2': 0.035, 'r2_full': 0.035, 'r2_const': 0.017, 'energy': 0.891, 'fit_r2': 0.164, 'ynorm': 8.047, 'pnorm': 2.463, 'use': False, 'n': 5817}
59 {'lam': 3.0, 'r2': 0.008, 'r2_full': -0.003, 'r2_const': 0.004, 'energy': 0.429, 'fit_r2': 0.046, 'ynorm': 0.921, 'pnorm': 0.125, 'use': False, 'n': 5817}

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Served single-turn generation (run as CMD of tools/gpu0_session.sh; no agent rollout): for mid-episode calls of
held-out stage-1 tasks, what the model writes from the start of the call
  reference  : unedited model, logged prompt
  prompt_I1  : unedited model, the instruction paragraph I1 inserted at the end of the first user message
  each ADAPTER_DIR : edited model, logged prompt
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has the shape of tools/vgen.py (arms: [{name, rows: [{ids}]}]) so interp/toolcall_check.py reads it.
"""
import argparse
import json
import os
import statistics
import sys
import time
from concurrent.futures import ThreadPoolExecutor

A_DIR = "/home/keith/gemma-v2/wsp31/authors/claude"
TOOLS = "/home/keith/gemma-v2/wsp31/tools"
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scratch/job9/gen.json [F20]
   17 episodes, 17 generated answers, 17 with a complete tool call
   1. unpaired string delimiter: 0 of 17 tool calls = 0.0% (unedited 0.7% to 1.1%, mark 3%; chance of 0 or more at the highest unedited rate 1): tool-call syntax UNDECIDED
      no verdict: NOT BROKEN needs 60 tool calls and a share below 3%; BROKEN needs a share of 3% or more and a chance of 0.001 or less for the calls
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close11_H23.log
Sat Nov 14 10:04:32 AM EST 2026

Sat Nov 14 10:09:14 AM EST 2026
keith     548097  0.0  0.0   8372  2496 ?        S    10:00   0:00 flock /home/keith/gemma-v2/wsp31/gpu0.lock timeout 1300 code/gpu_hold11b.sh
keith     548099  0.0  0.0  17652  8016 ?        S    10:00   0:00 timeout 1300 code/gpu_hold11b.sh
keith     548100  0.0  0.0  10136  4292 ?        S    10:00   0:00 /bin/bash code/gpu_hold11b.sh
keith     558453  0.0  0.0   8372  2496 ?        S    10:04   0:00 flock /home/keith/gemma-v2/wsp31/gpu0.lock timeout 520 code/gpu_hold11c.sh
keith     567775  0.0  0.0  17784  7940 ?        S    10:07   0:00 timeout 240 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/tools/closeprobe.py --adapter /home/keith/gemma-v2/wsp31/authors/claude/scratch/job11/ad/Q20 --out /hom
keith     567776  110 12.9 106300892 24991464 ?  Rl   10:07   1:33 /home/keith/gemma-v2/tii-venv/bin/python /home/keith/gemma-v2/wsp31/tools/closeprobe.py --adapter /home/keith/gemma-v2/wsp31/authors/claude/scratch/job11/ad/Q20 --out /home/keith/gemm
4:GPU0 (no server; run under the gpu0 lock; about 5 s per call record and arm, the reference arm is cached).
72:    ap.add_argument("--no-cache", action="store_true")
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scratch/data:
total 12
drwxrwxr-x  3 keith keith 4096 Nov 14 10:06 .
drwxrwxr-x 12 keith keith 4096 Nov 14 10:05 ..
drwxrwxr-x  2 keith keith 4096 Nov 14 10:06 cache

scratch/job11:
total 79216
drwxrwxr-x  3 keith keith     4096 Nov 14 10:03 .
drwxrwxr-x 12 keith keith     4096 Nov 14 10:05 ..
drwxrwxr-x 13 keith keith     4096 Nov 14 10:00 ad
-rw-rw-r--  1 keith keith 17571533 Nov 14 09:58 eval.pt
-rw-rw-r--  1 keith keith 11734489 Nov 14 10:03 eval_g.pt
-rw-rw-r--  1 keith keith 51746698 Nov 14 09:54 mk_stats.pt
-rw-rw-r--  1 keith keith    22387 Nov 14 09:54 mk_table.json
-rw-rw-r--  1 keith keith     8305 Nov 14 09:58 summary.json
-rw-rw-r--  1 keith keith     5487 Nov 14 10:03 summary_g.json

record fcv-brief-exact3-b20 ok
title (140 chars): Instruction pair vector with the 'be exact about what the issue asks' part written three times (layers 6 to 24), think-briefly part at dose 
   ## Hypothesis 4596 chars 
   ## Exact recipe 4754 chars 
   ## Prediction (written before the run) 1252 chars 
- not run (no time left in the hold); the only numbers are the 8 closes of the table above.
record mk-pair-global-b20 ok
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   ## Hypothesis 6618 chars 
   ## Exact recipe 5851 chars 
   ## Prediction (written before the run) 1366 chars 
- not run (no time left in the hold); the only numbers are the 8 closes of the table above.
Sat Nov 14 10:09:42 AM EST 2026

Sat Nov 14 10:11:50 AM EST 2026
change of log p(close) at close: mean +0.063, raised at 0.900 of 40 positions
change of log p(close) at cont: mean +0.650, raised at 0.595 of 126 positions
edit      cont  800+      n=   1  log p(close)   -5.381  top is close 0.000  log p(logged)   -0.006  top is logged 1.000
change of log p(close) at close: mean +0.063, raised at 0.900 of 40 positions
change of log p(close) at cont: mean +0.650, raised at 0.595 of 126 positions
scratch/hold11_end
scratch/hold11_start
scratch/hold11a_end
scratch/hold11a_start
scratch/hold11b_end
scratch/hold11b_start
scratch/hold11c_start
server up after 73s (pid/pgid 578044, log /home/keith/gemma-v2/wsp31/authors/claude/scratch/logs/server_18400_1114_101017.log)
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reference close all       n=  40  log p(close)   -0.071  top is close 1.000  log p(logged)   -0.071  top is logged 1.000
reference cont  all       n= 126  log p(close)  -19.572  top is close 0.000  log p(logged)   -0.114  top is logged 0.992
edit      close all       n=  40  log p(close)   -0.008  top is close 1.000  log p(logged)   -0.008  top is logged 1.000
edit      cont  all       n= 126  log p(close)  -18.922  top is close 0.016  log p(logged)   -0.236  top is logged 0.913
change of log p(close) at close: mean +0.063, raised at 0.900 of 40 positions
change of log p(close) at cont: mean +0.650, raised at 0.595 of 126 positions
Sat Nov 14 10:14:28 AM EST 2026
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cmd rc=0
server 578044 stopped at 10:13:35, hold 198s

server up after 73s (pid/pgid 578044, log /home/keith/gemma-v2/wsp31/authors/claude/scratch/logs/server_18400_1114_101017.log)
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cmd rc=0
server 578044 stopped at 10:13:35, hold 198s
stored unedited reference (7 arms of 120 episodes): unpaired delimiter 0.7% to 1.1% of tool calls (in 3.4% to 8.6% of the episodes); loops 0.0 to 4.3 per 100 episodes (0.0% to 7.5% of long thoughts)
scratch/job11/gen.json [reference]
   17 episodes, 17 generated answers, 17 with a complete tool call
   1. unpaired string delimiter: 0 of 17 tool calls = 0.0% (unedited 0.7% to 1.1%, mark 3%; chance of 0 or more at the highest unedited rate 1): tool-call syntax UNDECIDED
scratch/job11/gen.json [prompt_I1]
   17 episodes, 17 generated answers, 17 with a complete tool call
   1. unpaired string delimiter: 0 of 17 tool calls = 0.0% (unedited 0.7% to 1.1%, mark 3%; chance of 0 or more at the highest unedited rate 1): tool-call syntax UNDECIDED
scratch/job11/gen.json [Q20]
   17 episodes, 17 generated answers, 17 with a complete tool call
   1. unpaired string delimiter: 0 of 17 tool calls = 0.0% (unedited 0.7% to 1.1%, mark 3%; chance of 0 or more at the highest unedited rate 1): tool-call syntax UNDECIDED
scratch/job11/gen.json [H23]
   17 episodes, 17 generated answers, 17 with a complete tool call
   1. unpaired string delimiter: 0 of 17 tool calls = 0.0% (unedited 0.7% to 1.1%, mark 3%; chance of 0 or more at the highest unedited rate 1): tool-call syntax UNDECIDED
scratch/job11/gen.json [Q20c]
   17 episodes, 17 generated answers, 17 with a complete tool call
   1. unpaired string delimiter: 0 of 17 tool calls = 0.0% (unedited 0.7% to 1.1%, mark 3%; chance of 0 or more at the highest unedited rate 1): tool-call syntax UNDECIDED
Sat Nov 14 10:14:35 AM EST 2026

ok
record mk-pair-global-b20 ok
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   ## Hypothesis 6618 chars 
   ## Exact recipe 7020 chars 
   ## Prediction (written before the run) 1774 chars 
- global layers, dose 2 (Q20): change of log p(close) at close: mean +0.063, raised at 0.900 of 40 positions; change of log p(close) at cont: mean +0.650, raised at 0.595 of 126 positions
62:base: champion generation 0
66:size: whole network 0.1662% over 7 matrices, largest matrix 3.1560%
68:control size: whole network 0.1662% over 7 matrices, largest matrix 3.1560%
148:predicted_gain_120: -5 to 7
Pre-test 2, thought ends, `tools/closeprobe.py` (40 logged closes, exact contexts; flag below -0.05):

- global layers, dose 2 (Q20): change of log p(close) at close: mean +0.063, raised at 0.900 of 40 positions; change of log p(close) at cont: mean +0.650, raised at 0.595 of 126 positions

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Pre-test 3, served single turns (`code/icv_gen.py` under `gpu0_session.sh`, port [port], no tool executed, no rollout;
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`toolcall_check.py`: reference: 0 of 17 tool calls = 0.0%; prompt_I1: 0 of 17 tool calls = 0.0%; Q20: 0 of 17 tool calls = 0.0%; H23: 0 of 17 tool calls = 0.0%; Q20c: 0 of 17 tool calls = 0.0% (unedited rollouts 0.7% to 1.1%; too few calls for the tool's verdict, which needs 60).
build.sh
ctrl
edit
record.md
Sat Nov 14 10:14:56 AM EST 2026
[This command modified 1 file you've previously read: rec_mk-pair-global-b20.template.md. Call Read before editing.]

1
record mk-pair-global-b20 ok
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   ## Hypothesis 6618 chars 
   ## Exact recipe 7020 chars 
   ## Prediction (written before the run) 1774 chars 
OK edit: 7 modules changed (of 7 present), r=8, max |dW|_F/|W|_F 0.03156 at 35.down_proj
OK ctrl: 7 modules changed (of 7 present), r=8, max |dW|_F/|W|_F 0.03156 at 35.down_proj
d8b2224945577b7d430b
d8b2224945577b7d430b
{
 "base_model_name_or_path": "/home/keith/gemma-v2/models/gemma-4-31b-it-qat-w4a16-ct",
 "bias": "none",
 "lora_alpha": 16,
 "lora_dropout": 0.0,
 "peft_type": "LORA",
 "r": 8,
 "target_modules": "^model\\.language_model\\.layers\\.\\d+\\.(self_attn\\.(q_proj|k_proj|v_proj|o_proj)|mlp\\.(gate_proj|up_proj|down_proj))$",
 "task_type": "CAUSAL_LM",
 "use_rslora": false
}
READY
build.sh
ctrl
edit
record.md
Sat Nov 14 10:15:16 AM EST 2026

record fcv-brief-exact3-b20 ok
title (134 chars): Instruction pair vector, 'be exact about what the issue asks' part written three times in layers 6 to 24, think-briefly part at dose 2
   ## Hypothesis 4596 chars 
   ## Exact recipe 6158 chars 
   ## Prediction (written before the run) 1252 chars 
- this entry (H23): change of log p(close) at close: mean +0.032, raised at 0.850 of 40 positions; change of log p(close) at cont: mean -0.040, raised at 0.405 of 126 positions
44:base: champion generation 0
48:size: whole network 0.6819% over 180 matrices, largest matrix 2.0319%
50:control size: whole network 0.6820% over 180 matrices, largest matrix 2.0360%
126:predicted_gain_120: -5 to 7
Thought ends, `tools/closeprobe.py` (40 logged closes, exact contexts; flag below -0.05):

- this entry (H23): change of log p(close) at close: mean +0.032, raised at 0.850 of 40 positions; change of log p(close) at cont: mean -0.040, raised at 0.405 of 126 positions

Served single turns (`code/icv_gen.py` under `gpu0_session.sh`, port [port], no tool executed, no rollout; mid-episode
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|---|---|---|---|---|---|---|---|---|
| unedited | 47 | 30 | - | 139 | - | 17 of 17 | 0 | 0 |
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edit
record.md
Sat Nov 14 10:16:46 AM EST 2026
14
queue/net-deep-gate-close-b05/READY
queue/net-deep-gate-close-b12/READY
queue/net-preedit-commit-b12/READY
queue/net-preedit-commit-close-b05/READY

643 NOTES.md
2.1G	scratch
612M	code/data
0
0, 2 MiB
queue/fcv-brief-exact3-b20:
READY
build.sh
ctrl
edit
record.md

queue/mk-pair-global-b20:
READY
build.sh
ctrl
edit
record.md
61:| 0049 | claude | mk-pair-global-b20 | queued_s1 | -5 to +7 |  |  |  | - |
62:| 0050 | claude | fcv-brief-exact3-b20 | queued_s1 | -5 to +7 |  |  |  | - |
Sat Nov 14 10:17:14 AM EST 2026