Turn 20 · grok

1→---
name: long-running-background-tasks
description: >-
  Required reading before you start, watch, or wait on anything that keeps running after you launch it — background jobs, watchers, scheduled loops, CI, pull requests, training runs, dev servers, long builds. Read it before you launch such work and before you report on its state. Saying where a running job stands counts as working on it. Use when: about to launch, supervise, inspect, diagnose, or report on work that keeps running after it is started.
---

# Working with long-running background tasks

Only submitting or queuing jobs is not sufficient to complete the task. The definition of done is the job has completed successfully and you have verified that it has produced all the expected outputs.
10→
This means you must see through the jobs completion by watching the job to ensure that its healthy, progressing, and working as intended.

## Tools available

There's two ways to watch jobs: monitor and loop. Decide which of the two you need, sometimes you need both.

### monitor — deterministic, actionable events

- Use a monitor when the event is a predicate a script can evaluate — an API response, an exit code, a port answering.
20→- Typical events: CI turning red, a PR comment or merge conflict, a PR becoming ready to merge, a dev server coming up or going down, a job reaching a terminal state.
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190→  command='J=1234567; p=; while :; do s=$(sacct -nXP -j $J -o State|head -1); s=${s%% *}; s=${s:-PENDING}; if [ "$s" != "$p" ]; then case $s in COMPLETED) echo "DONE: $J"; exit;; PENDING|RUNNING|CONFIGURING|COMPLETING|REQUEUED|SUSPENDED|RESIZING) [ -n "$p" ] && echo "ACTION_REQUIRED: $J $p -> $s";; *) echo "FAILED: $J $s"; exit 1;; esac; fi; p=$s; sleep 30; done',
  description="Watch training run"
)
```

Launch both, so that we know when the job completes. When the monitor reports that the job has completed, cancel both the monitor and the scheduler, then determine next steps. Then:
- If it succeeded, simply present the results to the user.
- If it failed, debug the issue thoroughly, then fix and relaunch the job with new monitors attached. Make sure to have a thorough understanding of the issue before resubmitting, since training jobs are expensive. But always relaunch jobs so you don't waste the user's time.

exit: 1
Sat Nov 14 08:33:02 PM EST 2026
---
TURN
grok 1794705032 20
---
LOG
2 /home/keith/gemma-v2/wsp31/authors/grok/scratch/gpu_pretest.log
---
START Sat Nov 14 08:31:10 PM EST 2026
waiting up to 2362s for gpu0.lock
---
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1:
total 16
drwxrwxr-x 4 keith keith 4096 Nov 14 20:26 .
drwxrwxr-x 4 keith keith 4096 Nov 14 20:26 ..
drwxrwxr-x 2 keith keith 4096 Nov 14 20:26 ctrl
drwxrwxr-x 2 keith keith 4096 Nov 14 20:26 edit

/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020:
total 16
drwxrwxr-x 4 keith keith 4096 Nov 14 20:25 .
drwxrwxr-x 4 keith keith 4096 Nov 14 20:26 ..
drwxrwxr-x 2 keith keith 4096 Nov 14 20:25 ctrl
drwxrwxr-x 2 keith keith 4096 Nov 14 20:25 edit
---
---

- C:\Users\Owner\wsp31_loop\work\grok/
  - code/
    - toolact_build.py
  - queue/
    - toolact-plus-007-g1/
      - build.sh
      - mode.json
    - toolact-plus-020/
      - build.sh
      - mode.json
  - scratch_exit.py
  - scratch_fail.py
  - scratch_gpu.sh
  - scratch_mix.py
  - scratch_note.py
  - scratch_rho.py
  - scratch_schema.py
  - scratch_schema2.py
  - scratch_size.py
  - scratch_tax.py
  - scratch_tools.py

exit: 0 [truncated: showing first/last 19.6 KB of 21.1 KB - full output at: C:\Users\Owner\.grok\sessions\C%3A%5CUsers%5COwner%5Cwsp31_loop%5Cwork%5Cgrok\01a1dcc1-9bbc-70d2-aba6-b95a58c89b8c\terminal\call-174c3219-9fcc-4e5d-ba8d-e2ad3138d1ce-12.log]
95:State the base of every edit in its recipe (`base: unedited` or `base: 0031`) and spread your edits across both. Every gain is quoted against the unedited model (the pooled unedited arms of the batch's serving setting); a 0031 edit runs as 0031 + your edit and must also beat 0031 alone to go on.
112:  `base: champion generation <k>` in the recipe section: the generation you built and pre-tested on.
208:| `record.md` | title line, then the sections `## Hypothesis`, `## Exact recipe`, `## Prediction (written before the run)` |
209:| `READY` | empty file, created last. The runner ignores a directory without it and never re-reads one with it. |
217:`record.md` starts with `title: <one line, no | character>`. The prediction section must contain a line
218:`predicted_gain_120: <low> to <high>` (tasks gained over the reference arm, which is the champion, on the
223:Before you write `READY`: run the checker on `edit/` and `ctrl/`, and run the cheap pre-tests in `TOOLS.md`
---- SECTION ----
# 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
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- 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.

exit: 0
==== toolact-plus-020 edit
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{"mechanism": "tool_act always-on neuron", "alpha": 0.02, "cap_rho": 0.45, "capped": [[1, 0.1679, 0.45], [11, 0.5418, 0.45]], "neuron": "third", "ctrl": false, "seed": 71000, "neurons": [11815, 15193, 13714, 4707, 17853, 16167, 1300, 14789, 14106, 10223, 14753, 19421, 20529, 2887, 7827, 3292, 10308, 20850, 14035, 8524, 9026, 10838, 16143, 15854, 16292, 4991, 18852, 7189, 7725, 9366, 9712, 13536, 8366, 4283, 989, 13391, 15416, 5590, 14712, 9102, 9561, 6207, 13065, 1646, 6993, 13001, 15739, 14673, 18196, 19862, 5022, 12856, 13875, 350, 8085, 16983, 10215, 6036, 12505, 16519], "rho": [0.060037845826729455, 0.4500000005004194, 0.28536380603061273, 0.24222247278652137, 0.3653857843957743, 0.2310279132127395, 0.36496718708839126, 0.15626232136407311, 0.12800940866758198, 0.23717443920180767, 0.2259673641881126, 0.4500000272140608, 0.3255576473089026, 0.34467015766422443, 0.22214537939787052, 0.1404098284265702, 0.2727646073675251, 0.35986805112835774, 0.2256636572646319, 0.20871529600288963, 0.18624056542644601, 0.2026208732356799, 0.17402372144482872, 0.12165214573325199, 0.1155377029193425, 0.11189110228591574, 0.11846752511168748, 0.10162891226903549, 0.08897569341953732, 0.08368653969819889, 0.10277580152025308, 0.12265013220523953, 0.13270146048002232, 0.13873214951835683, 0.1376586102098904, 0.10260611976327474, 0.09756367658181189, 0.1082974133438104, 0.07759559454771349, 0.049450263999135755, 0.038112270444342185, 0.053409308490012665, 0.09651496022421636, 0.08714641844461839, 0.08569156853100639, 0.08812521520905421, 0.07935154099653875, 0.06528976179950557, 0.06646958866772862, 0.06560526503001322, 0.060120551586308794, 0.04612070313370598, 0.02569038681215116, 0.03164140019457131, 0.03309124894840702, 0.03143959867359685, 0.030948173685642143, 0.029027972662032647, 0.03082425505260731, 0.025682754197579056], "source_dir": "wsp31/interp/dirs/out/tool_act.pt", "fit": "tasks with int(sha1(instance_id)[:8],16) % 5 in {0,1,2}", "contrast": "tool_act", "base_weights"
: "unedited"}
==== toolact-plus-020 ctrl
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{"mechanism": "tool_act always-on neuron", "alpha": 0.02, "cap_rho": 0.45, "capped": [[1, 0.1679, 0.45], [11, 0.5418, 0.45]], "neuron": "third", "ctrl": true, "seed": 71000, "neurons": [11815, 15193, 13714, 4707, 17853, 16167, 1300, 14789, 14106, 10223, 14753, 19421, 20529, 2887, 7827, 3292, 10308, 20850, 14035, 8524, 9026, 10838, 16143, 15854, 16292, 4991, 18852, 7189, 7725, 9366, 9712, 13536, 8366, 4283, 989, 13391, 15416, 5590, 14712, 9102, 9561, 6207, 13065, 1646, 6993, 13001, 15739, 14673, 18196, 19862, 5022, 12856, 13875, 350, 8085, 16983, 10215, 6036, 12505, 16519], "rho": [0.060037845826729455, 0.4500000005004194, 0.28536380603061273, 0.24222247278652137, 0.3653857843957743, 0.2310279132127395, 0.36496718708839126, 0.15626232136407311, 0.12800940866758198, 0.23717443920180767, 0.2259673641881126, 0.4500000272140608, 0.3255576473089026, 0.34467015766422443, 0.22214537939787052, 0.1404098284265702, 0.2727646073675251, 0.35986805112835774, 0.2256636572646319, 0.20871529600288963, 0.18624056542644601, 0.2026208732356799, 0.17402372144482872, 0.12165214573325199, 0.1155377029193425, 0.11189110228591574, 0.11846752511168748, 0.10162891226903549, 0.08897569341953732, 0.08368653969819889, 0.10277580152025308, 0.12265013220523953, 0.13270146048002232, 0.13873214951835683, 0.1376586102098904, 0.10260611976327474, 0.09756367658181189, 0.1082974133438104, 0.07759559454771349, 0.049450263999135755, 0.038112270444342185, 0.053409308490012665, 0.09651496022421636, 0.08714641844461839, 0.08569156853100639, 0.08812521520905421, 0.07935154099653875, 0.06528976179950557, 0.06646958866772862, 0.06560526503001322, 0.060120551586308794, 0.04612070313370598, 0.02569038681215116, 0.03164140019457131, 0.03309124894840702, 0.03143959867359685, 0.030948173685642143, 0.029027972662032647, 0.03082425505260731, 0.025682754197579056
[... 4650 characters cut ...]

exit: 0
===== TOOLS headings =====
1:# wsp31 tools for edit authors
22:## 1. Edit format (what `edit/` and `ctrl/` must be)
60:## 2. Building an edit and its matched control
85:### Training-sized edits (most layers, 0.3% to 3% of the whole network)
116:## 3. GPU 0: the only way to use it
140:### g31.py: this lane's forward pass of the 31B model (library)
159:## 4. The champion (design against it, pre-test on it)
188:## 5. Cheap pre-tests
190:### Before you submit: does the edit break ordinary behaviour?
256:## 6. Stored trajectories and request logs
280:## 7. Traps (each one cost this lane time)
308:## 8. Not available yet
===== REPORT first 80 =====
# Interpretability lane: what is known about the inside of Gemma 4 31B

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    against 6,646 and 6,693): 220 of its calls carry no tool call (unedited: 1 and 1). 115 episodes end with an empty
    patch. So multiplying the end-of-thought write by 25 does not make the model stop thinking and act: the thought
    closes and what follows is no longer a tool call.
  - **0007, what it does (supplementary, not part of the registered verdict).** Solved gained 7 and lost 8 against
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exit: 0 [truncated: showing first/last 19.6 KB of 20.0 KB - full output at: C:\Users\Owner\.grok\sessions\C%3A%5CUsers%5COwner%5Cwsp31_loop%5Cwork%5Cgrok\01a1dcc1-9bbc-70d2-aba6-b95a58c89b8c\terminal\call-3748daf4-5003-4dc9-a9de-4d308797b6ca-19.log]
===== TOOLS 188-310 =====
## 5. Cheap pre-tests

### Before you submit: does the edit break ordinary behaviour?

Stage 1 so far (provisional): 0008 -10, 0011 -10, 0012 -21 tasks, 0015 +6 (inside control noise). The harmful arms
did not cut calls or drop tool calls; they made more calls (+9% to +32%), longer ORDINARY thoughts (median thought
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flips and the push to close inside thoughts did not rank the four edits (`REPORT.md` section 8). What did:
1. **Thought ends** (forward pass, about 2 min): `closeprobe.py --adapter EDIT`, line "change of log p(close) at
   close". 0011 -0.11, 0012 -0.52 (harmful), 0015 +0.04, controls -0.002 to +0.001. **Below -0.05: your edit makes
   the agent less ready to end the thoughts it ends today; expect longer ordinary thoughts.** Chosen after the
   results on four edits; tested prospectively on b004 (0021 flagged at -0.20, 0020 not, before the score). It
   does not see 0008's harm (-0.003).
2. **Tool-call syntax** (CPU, interpretability lane): `python3 $R/wsp31/interp/toolcall_check.py OUT.json` on the
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   unedited 0.7% to 1.1%, 0011 19.7%, 0012 31.4%, 0008 0.7%, 0015 0.8%; exit code 3 = BROKEN. Needs 100 single
   tool calls or 8 whole episodes; the FIRST call of an episode never shows the break (generate from later calls).
[... 218 lines cut ...]
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    by = {}
    for item in filter(None, (a.ablate or "").split(",")):
        l, j = item.split(":")
        by.setdefault(int(l), []).append((int(j), 0.0))
    for item in filter(None, (a.scale or "").split(",")):
        l, j, s = item.split(":")

exit: 0
===020
#!/bin/bash
# Rebuild edit/ and ctrl/ bit for bit. CPU only.
set -euo pipefail
cd /home/keith/gemma-v2/wsp31/authors/grok
PY=/home/keith/gemma-v2/tii-venv/bin/python
$PY code/toolact_build.py queue/toolact-plus-020 edit --stream-frac 0.02 --cap-rho 0.45 --neuron third --seed 71000
$PY code/toolact_build.py queue/toolact-plus-020 ctrl --stream-frac 0.02 --cap-rho 0.45 --neuron third --seed 71000
===007
#!/bin/bash
# Rebuild edit/ and ctrl/ bit for bit. CPU only. Reads unedited checkpoint columns for the fourth-quietest neuron.
set -euo pipefail
cd /home/keith/gemma-v2/wsp31/authors/grok
PY=/home/keith/gemma-v2/tii-venv/bin/python
$PY code/toolact_build.py queue/toolact-plus-007-g1 edit --stream-frac 0.02/3 --cap-rho 0.15 --neuron fourth --seed 71000
$PY code/toolact_build.py queue/toolact-plus-007-g1 ctrl --stream-frac 0.02/3 --cap-rho 0.15 --neuron fourth --seed 71000
===chmod
CHECK toolact-plus-020 edit
OK edit: 180 modules changed (of 180 present), r=1, max |dW|_F/|W|_F 0.0906 at 1.down_proj
[... 13 lines cut ...]
saved queue/toolact-plus-007-g1/edit r 1 modules {'0.down_proj': {'rank': 1, 'fro': 0.4232129988849393, 'rel_fro': 0.005641059802486801}, '0.gate_proj': {'rank': 1, 'fro': 1.0406200740511173, 'rel_fro': 0.007202585487916761}, '0.up_proj': {'rank': 1, 'fro': 0.8812782627613143, 'rel_fro': 0.006093684355298196}, '1.down_proj': {'rank': 1, 'fro': 2.2008628543547015, 'rel_fro': 0.030551047650729635}, '1.gate_proj': {'rank': 1, 'fro': 0.8352784881923175, 'rel_fro': 0.005890811518385418}, '1.up_proj': {'rank': 1, 'fro': 0.7387919872377855, 'rel_fro': 0.005210681609817866}, '2.down_proj': {'rank': 1, 'fro': 1.112054387413481, 'rel_fro': 0.01456721167738217}, '2.gate_proj': {'rank': 1, 'fro': 1.0924598837408517, 'rel_fro': 0.007816892988727293}, '2.up_proj': {'rank': 1, 'fro': 0.8285795022601239, 'rel_fro': 0.005932219459586529}, '3.down_proj': {'rank': 1, 'fro': 0.7678716293194624, 'rel_fro': 0.01014448689260209}, '3.gate_proj': {'rank': 1, 'fro': 0.9166787646857945, 'rel_fro': 0.006111706067850518}, '3.up_proj': {'rank': 1, 'fro': 0.7095468291946558, 'rel_fro': 0.00473479146359338}, '4.down_proj': {'rank': 1, 'fro': 2.0225886583995356, 'rel_fro': 0.026895571593740158}, '4.gate_proj': {'rank': 1, 'fro': 0.8753429710345587, 'rel_fro': 0.006013255781603923}, '4.up_proj': {'rank': 1, 'fro': 0.6794935605152926, 'rel_fro': 0.004668004431796157}, '5.down_proj': {'rank': 1, 'fro': 0.8078574162092066, 'rel_fro': 0.011317933623872341}, '5.gate_proj': {'rank': 1, 'fro': 0.9439240485348542, 'rel_fro': 0.006278339468729434}, '5.up_proj': {'rank': 1, 'fro': 0.6578846951743523, 'rel_fro': 0.004376464767416968}, '6.down_proj': {'rank': 1, 'fro': 1.6845967851072792, 'rel_fro': 0.023242487509546498}, '6.gate_proj': {'rank': 1, 'fro': 0.9035571027086228, 'rel_fro': 0.005901699477949271}, '6.up_proj': {'rank': 1, 'fro': 0.685887026640462, 'rel_fro': 0.004482768896582286}, '7.down_proj': {'rank': 1, 'fro': 0.6205032136281464, 'rel_fro': 0.008417391301723193}, '7.gate_proj': {'rank': 1, 'fro':
 1.0729685471882107, 'rel_fro': 0.007247587562633566}, '7.up_proj': {'rank': 1, 'fro': 0.8297683609933826, 'rel_fro': 0.005604408851086022}, '8.down_proj': {'rank': 1, 'fro': 0.6097701062453579, 'rel_fro': 0.007986562962243354}, '8.gate_proj': {'rank': 1, 'fro': 1.035264441156411, 'rel_fro': 0.007227061338066089}, '8.up_proj': {'rank': 1, 'fro': 0.8439185265208804, 'rel_fro': 0.005887683284397371}, '9.down_proj': {'rank': 1, 'fro': 0.84256978594455, 'rel_fro': 0.010968362127278948}, '9.gate_proj': {'rank': 1, 'fro': 1.0478927827175424, 'rel_fro': 0.007181797023049212}, '9.up_proj': {'rank': 1, 'fro': 0.8095877409440377, 'rel_fro': 0.005546801033459284}, '10.down_proj': {'rank': 1, 'fro': 0.7620326525233452, 'rel_fro': 0.010595203547353585}, '10.gate_proj': {'rank': 1, 'fro': 1.0528567912946787, 'rel_fro': 0.006952167607063503}, '10.up_proj': {'rank': 1, 'fro': 1.0311814175814646, 'rel_fro': 0.00680792676905679}, '11.down_proj': {'rank': 1
[... 13005 characters cut ...]

3930→--- all names ---
[None, None, None, None, None, None, None, None, None, None, None, None, None, None]


### Turn 64 (Assistant)
[tool_request: search_replace]
- file_path: C:\Users\Owner\wsp31_loop\work\grok\scratch_mix.py
- new_string: #!/usr/bin/env python3
"""Tool-family mix on x005 base: solved vs finished test-fail vs cutoff."""
import json, collections, re
3940→
P = "/home/keith/gemma-v2/results/wsp31/batches/x005/base/rebench/shard0_gpu0/task_results.jsonl"
rows = [json.loads(l) for l in open(P) if l.strip()]

def kind(r):
    g = r.get("grade") or {}
    err = g.get("error") or ""
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    cutoff = ot >= 19000
    empty = (r.get("patch_chars") or 0) == 0 or "Empty agent patch" in err
[... 172 lines cut ...]
P = "/home/keith/gemma-v2/results/wsp31/batches/x005/base/rebench/shard0_gpu0/task_results.jsonl"
rows = [json.loads(l) for l in open(P) if l.strip()]
TEST_RE = re.compile(r"\b(pytest|py\.test|unittest|tox|nose2|trial|stestr)\b", re.I)

def kind(r):
    g = r.get("grade") or {}
    err = g.get("error") or ""
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<workspace_result workspace_path="C:\Users\Owner\wsp31_loop\work\grok">
Found at least 20 matching lines
C:\Users\Owner\.grok\sessions\C%3A%5CUsers%5COwner%5Cwsp31_loop%5Cwork%5Cgrok\01a1dcc1-9bbc-70d2-aba6-b95a58c89b8c\compaction\segment_000.md
37:- Entry 1 slug `toolact-plus-020`: base unedited / champion generation 0. Always-on MLP bake of confirmed tool_act PLUS direction at stream fraction 0.02, rho cap 0.45, neuron = third-smallest absact (0031's neuron). Training-sized.
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49:- Failure taxonomy on x005 base (budget 20000, 120 tasks, solved 75): finished test-fail 26, cutoff 17 (empty 7 of those plus patch; 10 of 17 never test, 4 never edit), finished empty 2. Solved vs test-fail tool mix is almost identical (mean edits ~2.43 vs 2.54, runs ~13.59 vs 12.46, tests ~2.03 vs 2.04, reads ~7.47 vs 8.08). Cutoffs read more (mean reads 17.41, runs 19.29, tests 1.12). So "run more tests" does not separate the 26 wrong-patch failures. The behavioural gap that tool_act plus can hit is cutoffs that over-read and under-edit. Hypothesis: push tool choice toward edit/write. The minus sign was NOT queued: plus had the larger confirmed hook effect (+14 vs about −3 nat) and cutoffs under-edit.
56:Examined (read-only, wrx90) earlier this turn: BRIEF.md, RESULTS.md (grok had nothing queued; last prior turn "retry at 23:01" but THIS turn is open via .turn_start and TURN_OPEN.d/grok — user still wants the submission), STATUS.md, CHAMPION.md (gen 1 = 0031; kh001 running, record 0072), TOOLS.md, netops.py write_dir, edits.py EditSet, LEDGER through 0073, survey section C, interp REPORT.md / ATLAS.md (close_thought and tool_act confirmed as hooks; episode-level solved/tests_run/patch/finished/brief are weak), runner.py declared_base ~1255 and s1_lane, loop.conf, stage_promote.py, claude thinklib.py clipdiv/signflip, icv_job.py build_arm lines 237–264, x005/x003/x001/b001 result traces (ATIF-v1.7; tool field is function_name, not name).
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67:"""Bake the confirmed tool_act residual direction as an always-on MLP neuron.
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78:TOOL = f"{R}/wsp31/interp/dirs/out/tool_act.pt"
115:        raise SystemExit(f"tool_act direction at layer {L} is zero")
269:- Entry 1: `base: unedited` THEN `base: champion generation 0`. `mode: solo`. size line from train_size percents. Hypothesis: x005 taxonomy numbers above; tool_act hook never baked; different from close-gates, code-vs-prose, and 0031's instruction paragraph. Recipe: script path and args, sources (tool_act.pt, icv_stats reused not refit, net_stats only to verify neuron rank), clipdiv, rho cap and the two scale factors, seed 71000+L, neuron rule, fitted-on sentence (interp fit rule; 38 vs 735; author did not refit and did not use stage-2; neuron stats reused from claude turn-3 / ledger 0031's 35 fit calls). Intended vs built: hook adds alpha*position stream norm*unit after every layer; built is 2% of the MEAN stream norm, constant, one MLP neuron, layers 1 and 11 scaled, attention not written. Control: signflip, same neurons, same gate/up, same |coordinate| magnitudes. Warning: this neuron IS 0031's; screening must be unedited; stacking would break the read.
282:NOTES.md still absent. Rewrite at the end, under 600 words: learned (test-fail vs solved tool mix the same; cutoffs over-read; tool_act hook never baked; rho cap on L1 and L11; do not reuse 0031's neuron on a 0031 stack; GPU status), what was queued, what not to repeat (thought-close, end-neuron scale, another brevity ICV, spec-audit clone, code-style damp), what next would be (if both null, the hook does not bake; if high dose harmful and low dose null, lower stream frac; if only unedited gains, the push overlaps 0031; minus sign still untested).
296:Solved: what has already failed; champion is 0031; two-base runner logic (first matching base line); remaining failure split at 20k (26 wrong finished patches with the same tool mix as so
[... 2306 characters cut ...]

2588→exit: 0
   146 /home/keith/gemma-v2/wsp31/interp/ATLAS.md
2590→   438 /home/keith/gemma-v2/wsp31/interp/ATLAS_lens.md
    62 /home/keith/gemma-v2/tii-wsp31-doc/research/wsp31/PRIOR_E4B.md
   646 total
===== ATLAS =====
# ATLAS: located and causally checked parts of Gemma 4 31B

Lane `wsp31/interp`. Only entries that were located **and** changed the model at agent decision points in a causal
test on tasks they were not fitted on are listed under "Confirmed". Everything else is under "Unconfirmed".

## Changelog
2600→- 7:39 AM ET, Fri 13 Nov 2026: holds 7 to 12 evaluated (REPORT 3.5.1). Entry 1 extended: the close direction is **confirmed on layers
  20-59** (0.3% and 1% per layer) **and on layers 30-48** (1%); layers 0-19 are not needed. **Second confirmed
  entry:** the tool-choice direction `tool_act` on layers 0-59 at 2% per layer (not at 1%; not confirmed on layers
  20-59 at 0.3% and 1%). `finished` and `solved`: dose curves only, unconfirmed. Hooked forward passes, no weight
  edit, no rollout.
- Fri 13 Nov 2026, 1:06 AM ET: **first confirmed entry**: the close-the-thought direction on layers 0-59 passes the
  dose check with the clean control (amendment 3g) at 1% of the stream norm per layer: +6.2 nat at goes-on points
  and -11.8 nat at real closes against the stronger control, 10 of 10 held-out episodes each; incoherent at 2%.
[... 92 lines cut ...]
2700→
Only submitting or queuing jobs is not sufficient to complete the task. The definition of done is the job has completed successfully and you have verified that it has produced all the expected outputs.
10→
This means you must see through the jobs completion by watching the job to ensure that its healthy, progressing, and working as intended.

## Tools available

There's two ways to watch jobs: monitor and loop. Decide which of the two you need, sometimes you need both.

exit: 0
===== GPU LOG =====
START Sat Nov 14 08:31:10 PM EST 2026
waiting up to 2362s for gpu0.lock
GOT_LOCK Sat Nov 14 08:34:47 PM EST 2026
RUN --adapter
Traceback (most recent call last):
  File "/home/keith/gemma-v2/wsp31/tools/causal.py", line 169, in <module>
    main()
    ~~~~^^
  File "/home/keith/gemma-v2/wsp31/tools/causal.py", line 160, in main
    r = run(a)
  File "/home/keith/gemma-v2/wsp31/tools/causal.py", line 111, in run
    m = m or g31.G31(device=a.device)
             ~~~~~~~^^^^^^^^^^^^^^^^^
  File "/home/keith/gemma-v2/wsp31/tools/g31.py", line 141, in __init__
[line removed by the dashboard scrubber]
               ~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.62 GiB. GPU 0 has a total capacity of 95.01 GiB of which 1.25 GiB is free. Process 2363154 has 93.20 GiB memory in use. Including non-PyTorch memory, this process has 550.00 MiB memory in use. Of the allocated memory 0 bytes is allocated by PyTorch, and 0 bytes is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
DONE --adapter rc=1
[... 94 lines cut ...]
2664:| tool_act +0.3 real | 39.0 | -39.2 | 1.000 | -30.71 / -15.35 | | +43.4 |
9:  entry:** the tool-choice direction `tool_act` on layers 0-59 at 2% per layer (not at 1%; not confirmed on layers
15:  A hooked forward pass, not a weight edit or a rollout. tool_act and the smaller layer sets are queued.
20:  layer `close_thought` moves log p(close) by +9.3 nat at goes-on points and -13.0 nat at real closes, `tool_act`
25:  in-thought newline points does not differ between cut-off and finished episodes (AUC 0.52 on 136 episodes,
[line removed by the dashboard scrubber]
84:- **Effect at 2% per layer (coherent: KL 0.52 nat for plus, 0.45 for minus):** plus +14.3 nat, 10.46 nat more than
110:| tool_act: next tool is edit or write, against read or run | tool-name points, episode mean removed | 0.849 (0.527); 0.94 at L20, 0.98 at L24, 1.000 at L58; size 4% of the stream norm at L0 to 44% at the top | read-out only; at 1% per layer on layers 0-59 the tool log-odds moved by +6.8 nat (plus) and -2.5 nat (minus) against -0.7 nat for the registered null and +0.8 to +1.6 nat for unrelated pushes (REPORT 3.5); the run with the clean control is queued; not confirmed |

exit: 0
===== nvidia =====
pid, process_name, used_gpu_memory [MiB]
2363154, VLLM::EngineCore, 95434 MiB
2466048, VLLM::EngineCore, 95312 MiB
===== pid =====
2363154    01:00:05 keith    VLLM::EngineCore
===== lock =====
-rw-rw-r-- 1 keith keith 0 Nov 12 19:07 /home/keith/gemma-v2/wsp31/gpu0.lock
===== parents =====
2363154 2359351    01:00:05 VLLM::EngineCore
2359351       1    01:00:12 /home/keith/gemma-v2/tii-venv/bin/python -m vllm.entrypoints.openai.api_server --model /home/keith/gemma-v2/models/gemma-4-31b-it-qat-w4a16-ct --served-model-name base gemma-4-31b --host [ip] --port [port] --
===== causal outs =====
none
===== date =====
Sat Nov 14 08:38:01 PM EST 2026

1→#!/usr/bin/env python3
import json, os, subprocess, sys
R = "/home/keith/gemma-v2"
PY = f"{R}/tii-venv/bin/python"
T = f"{R}/wsp31/tools"
base = f"{R}/wsp31/authors/grok"
os.environ["WSP31_WORK"] = f"{base}/scratch"
# source env is not needed if PY is absolute
pairs = [
10→    "queue/toolact-plus-020",
    "queue/toolact-plus-007-g1",
]
for q in pairs:
    for part in ("edit", "ctrl"):
        d = f"{base}/{q}/{part}"
        if not os.path.isdir(d):
            print("MISSING", d)
            continue
        c = subprocess.run([PY, f"{T}/check_adapter.py", d], capture_output=True, text=True)
20→        print("CHECK", q, part, c.returncode, (c.stdout or c.stderr).strip()[:300])
        out = f"{base}/scratch/size_{q.split('/')[-1]}_{part}.json"
        s = subprocess.run([PY, f"{T}/train_size.py", out, f"mine={d}"], capture_output=True, text=True)
        print("SIZE_RC", s.returncode, (s.stdout or "")[-400:], (s.stderr or "")[-200:])
        if os.path.exists(out):
            data = json.load(open(out))
            # print the mine block compactly
            mine = data.get("mine") or data
            if isinstance(mine, dict):
[line removed by the dashboard scrubber]
[line removed by the dashboard scrubber]
                print("MINE", json.dumps(mine)[:800])

1→#!/usr/bin/env python3
"""Bake the confirmed tool_act residual direction as an always-on MLP neuron.

The direction is the interp lane's mean difference at tool-name points
[line removed by the dashboard scrubber]
Plus points toward edit or write. This script does not refit it.

One neuron per layer is replaced. Its gate and up rows are the always-on read
[line removed by the dashboard scrubber]
10→the same rows, so the activation stays near `gbar`. Its down column is set so
that, at activation gbar, the residual stream gains

    alpha * mean_stream_norm[L] * unit(dir[L])

after the post-feedforward norm and the layer scalar. The conversion is
clipdiv from thinklib (zero the 5% of coordinates with the smallest |w_post|).

Control: the same neuron and the same per-coordinate magnitudes, with the sign
of every coordinate of the stream target flipped (seed + layer) before clipdiv.
20→
[... 12 lines cut ...]
ICV = f"{R}/wsp31/authors/claude/code/data/icv_stats.pt"
NET = f"{R}/wsp31/authors/claude/scratch/job3/net_stats.pt"
TOOL = f"{R}/wsp31/interp/dirs/out/tool_act.pt"
D = 5376


def clipdiv(d, wp, q=0.05):
40→    a = wp.abs().float()

exit: 0
===== files =====
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020:
total 32
drwxrwxr-x 4 keith keith 4096 Nov 14 20:40 .
drwxrwxr-x 4 keith keith 4096 Nov 14 20:26 ..
-rwxr-xr-x 1 keith keith  398 Nov 14 20:36 build.sh
drwxrwxr-x 2 keith keith 4096 Nov 14 20:25 ctrl
drwxrwxr-x 2 keith keith 4096 Nov 14 20:25 edit
-rw-r--r-- 1 keith keith   47 Nov 14 20:36 mode.json
-rw-r--r-- 1 keith keith 7884 Nov 14 20:40 record.md

/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/ctrl:
total 9540
drwxrwxr-x 2 keith keith    4096 Nov 14 20:25 .
drwxrwxr-x 4 keith keith    4096 Nov 14 20:40 ..
-rw-rw-r-- 1 keith keith     371 Nov 14 20:25 adapter_config.json
-rw------- 1 keith keith 9728808 Nov 14 20:25 adapter_model.safetensors
-rw-rw-r-- 1 keith keith   21046 Nov 14 20:25 edit.json

[... 16 lines cut ...]
49:predicted_gain_120: -6 to +9
===== code =====
CODE_OK
NO_READY
TOUCH
-rw-rw-r-- 1 keith keith 0 Nov 14 20:40 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/READY
READY1_OK
Sat Nov 14 08:40:24 PM EST 2026

exit: 0
===== files before =====
total 32
drwxrwxr-x 4 keith keith 4096 Nov 14 20:41 .
drwxrwxr-x 4 keith keith 4096 Nov 14 20:26 ..
-rwxr-xr-x 1 keith keith  476 Nov 14 20:36 build.sh
drwxrwxr-x 2 keith keith 4096 Nov 14 20:26 ctrl
drwxrwxr-x 2 keith keith 4096 Nov 14 20:26 edit
-rw-r--r-- 1 keith keith   47 Nov 14 20:36 mode.json
-rw-r--r-- 1 keith keith 5268 Nov 14 20:41 record.md
===== headings =====
1:title: One-third tool_act plus on a fresh neuron, added on top of 0031
3:## Hypothesis
7:## Exact recipe
9:mode: solo
10:base: 0031
11:base: champion generation 1
13:size: whole network 0.7178% over 180 matrices, largest matrix 3.0555%
37:## Prediction (written before the run)
39:predicted_gain_120: -4 to +5
TOUCH
-rw-rw-r-- 1 keith keith 0 Nov 14 20:41 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/READY
READY2_OK
Sat Nov 14 08:41:03 PM EST 2026

exit: 0
===== queue =====
/home/keith/gemma-v2/wsp31/authors/grok/queue
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/build.sh
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/ctrl
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/edit
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/mode.json
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/READY
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/record.md
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/build.sh
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/ctrl
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/edit
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/mode.json
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/READY
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/record.md
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/REJECTED
===== notes words =====
504 /home/keith/gemma-v2/wsp31/authors/grok/NOTES.md
===== ready mtimes =====
2026-11-14 20:40:24.676904741 -0500 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/READY
2026-11-14 20:41:03.611453894 -0500 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/READY
2026-11-14 20:40:12.481732734 -0500 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/record.md
2026-11-14 20:41:00.575411072 -0500 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/record.md
2026-11-14 20:41:12.215575251 -0500 /home/keith/gemma-v2/wsp31/authors/grok/NOTES.md
===== no third =====
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1/
/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/
CLEANED
Sat Nov 14 08:41:26 PM EST 2026

exit: 0
===== REJECTED 020 =====
2026-11-14 20:40:31 EST
prediction section has no 'predicted_gain_120: <low> to <high>' line

===== REJECTED 007? =====
2026-11-14 20:41:31 EST
prediction section has no 'predicted_gain_120: <low> to <high>' line
===== mtimes =====
2026-11-14 20:40:31.755160090 -0500 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/REJECTED
2026-11-14 20:40:24.676904741 -0500 /home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-020/READY
===== status head =====
76:## Rejected entries (reason in the REJECTED file)
78:- `wsp31/authors/grok/queue/toolact-plus-007-g1`
79:- `wsp31/authors/grok/queue/toolact-plus-020`
===== date =====
Sat Nov 14 08:41:40 PM EST 2026

exit: 0
===== hits =====
/home/keith/gemma-v2/wsp31/throughput/runner_swa/suite/test_supp.py:182:                           f"## Exact recipe\n\nfake\n\n## Prediction (written before the run)\n\npredicted_gain_120: -4 to 9\n\n"
/home/keith/gemma-v2/wsp31/throughput/runner_swa/suite/test_supp.py:187:          "s2": s2, "verdict": verdict, "predicted_gain_120": [-4.0, 9.0], "record": rec, "base_gen": 0}
/home/keith/gemma-v2/wsp31/throughput/runner_swa/suite/test_supp.py:966:                                   + "\n\n## Prediction (written before the run)\n\npredicted_gain_120: -1 to 4\n" + "p" * 40 + "\n")
/home/keith/gemma-v2/wsp31/throughput/runner_spec/suite/test_supp.py:180:                           f"## Exact recipe\n\nfake\n\n## Prediction (written before the run)\n\npredicted_gain_120: -4 to 9\n\n"
/home/keith/gemma-v2/wsp31/throughput/runner_spec/suite/test_supp.py:185:          "s2": s2, "verdict": verdict, "predicted_gain_120": [-4.0, 9.0], "record": rec, "base_gen": 0}
/home/keith/gemma-v2/wsp31/throughput/runner_spec/suite/test_supp.py:964:                                   + "\n\n## Prediction (written before the run)\n\npredicted_gain_120: -1 to 4\n" + "p" * 40 + "\n")
/home/keith/gemma-v2/wsp31/throughput/runner_spec2/suite/test_supp.py:180:                           f"## Exact recipe\n\nfake\n\n## Prediction (written before the run)\n\npredicted_gain_120: -4 to 9\n\n"
/home/keith/gemma-v2/wsp31/throughput/runner_spec2/suite/test_supp.py:185:          "s2": s2, "verdict": verdict, "predicted_gain_120": [-4.0, 9.0], "record": rec, "base_gen": 0}
/home/keith/gemma-v2/wsp31/throughput/runner_spec2/suite/test_supp.py:964:                                   + "\n\n## Prediction (written before the run)\n\npredicted_gain_120: -1 to 4\n" + "p" * 40 + "\n")
/home/keith/gemma-v2/wsp31/interp/logs/qstate.py:7:          x.get("ready_time"), x.get("predicted_gain_120"))
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:481:        lo, hi = it["predicted_gain_120"]
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:539:        p = i["predicted_gain_120"]
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:554:        p = i["predicted_gain_120"]
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:608:    if not re.search(r"predicted_gain_120:\s*-?\d+(\.\d+)?\s*to\s*-?\d+(\.\d+)?", out[SECTIONS[2]]):
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:609:        return None, "prediction section has no 'predicted_gain_120: <low> to <high>' line"
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:692:            pred = re.search(r"predicted_gain_120:\s*(-?\d+(?:\.\d+)?)\s*to\s*(-?\d+(?:\.\d+)?)", rec["sections"][SECTIONS[2]])
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:693:            it["predicted_gain_120"] = [float(pred.group(1)), float(pred.group(2))]
/home/keith/gemma-v2/wsp31/work/budget_switch/run_new/runner.py:[port]:            lo, hi = it["predicted_gain_120"]
[... 31 lines cut ...]
/home/keith/gemma-v2/wsp31/authors/claude/code/finalize.py:4:prediction section (the behaviour predictions written by the author for this entry)."""
/home/keith/gemma-v2/wsp31/infra/block3/runner.py:489:        return None, "prediction section has no 'predicted_gain_120: <low> to <high>' line"
/home/keith/gemma-v2/wsp31/infra/runner_patch/runner.py:489:        return None, "prediction section has no 'predicted_gain_120: <low> to <high>' line"
/home/keith/gemma-v2/wsp31/infra/runner_patch/runner.base.py:489:        return None, "prediction section has no 'predicted_gain_120: <low> to <high>' line"
/home/keith/gemma-v2/wsp31/infra/runner_patch2/runner.py:489:        return None, "prediction section has no 'predicted_gain_120: <low> to <high>' line"
/home/keith/gemma-v2/wsp31/infra/runner_patch2/runner.base.py:489:        return None, "prediction section has no 'predicted_gain_120: <low> to <high>' line"
/home/keith/gemma-v2/tii-wsp31-doc/research/wsp
[... 280 characters cut ...]

exit: 0
===== SECTIONS and parse =====
    parked = [i for i in mine if i["state"] == "parked"]
    if parked:
        L += ["## Your parked entries (not screened)", "",
              "To put one back as an entry of this round, create an empty file `RESUBMIT` in its queue directory. It is served "
              "from the frozen copy, unchanged; a changed edit is a new entry under a new slug.", ""]
        L += [f"- {i['ledger_id']} `{i['slug']}`: {i['title']}" for i in parked] + [""]
    rej = sorted(p for n in ("REJECTED", "RESUBMIT_REFUSED") for p in (AUTH / a / "queue").glob("*/" + n) if p.stat().st_mtime > t0)
    if rej:
        L += ["## Not accepted since your last turn", ""]
        for p in rej:
            why = (p.read_text(errors="replace").splitlines() + ["", ""])[1][:300]
            L.append(f"- `{p.parent.name}` ({p.name}): {why}")
        L.append("")
    old = [i for i in mine if i.get("s1") and not new(i)]
    if old:
        L += ["## Your earlier scored entries", ""] + head + [row(i) for i in old] + [""]
    L += ["## The other authors' entries", ""] + (head + [row(i) for i in others] if others else ["None yet."]) + [""]
    return "\n".join(L)
[... 124 lines cut ...]
1184:    info = {"arms": len(refs), "mean": round(mean, 2), "tasks": len(common), "group": g, "drift": drift, "gains_unedited": gains_u}
1294:    """0031 alone vs unedited on the screen set: reference arms of the two bases in the same serving group, task set and
1353:                        f"the pool", "pool": {"arms": 1, "mean": sum(o.values()), "drift": True, "pool_mean": round(pm, 2)}, "drift": True}
1362:        gains[a["name"]] = round(sum(e[t] - sum(x[t] for x in refs) / len(refs) for t in ts), 2)
1364:    info = {"arms": len(refs), "mean": round(mean, 2), "tasks": len(common), "batches": sorted({p["batch"] for p in pool} | {b["name"]})}
1420:    ch = champion() if lane is None else champion_at(lane)   # two bases open (14 Nov): the lane's base
1458:    picked = [] if s2 else pick_round(lane_items(its, lane), n_pick, skip)   # one author's round
1903:    if b.get("kind") == "confirm" and b.get("master"):   # a part of a run: only this part starts again (at most 3 starts)

exit: 0
                 f"`{s['batch']}` ran in an image where they cannot be solved and were rerun in their right images for every arm "
                 f"of the batch (supplement `{cor['supp']}`, ledger record {cor['record']}): " + ", ".join(f"`{t}`" for t in cor["rerun"])
                 + f". Scored on {cor.get('final_n', 0) - len(cor.get('still_owed') or [])} of {cor.get('final_n', '?')} tasks of the final list"
                 + f". The numbers above are the corrected ones; as first scored the gain was {o['gain']:+.1f}"
                 + (f" ({o['edit_solved']} vs {o['base_solved']} solved)." if "edit_solved" in o else "."))
    pend = pending_rerun(it, stage)
    if pend:
        m = len(final_tasks(b.get("stage", stage)))
        L.append(f"- Provisional: batch `{s['batch']}` has {m - len(pend)} of the {m} tasks of the final stage-{stage[1]} list run "
                 f"validly in every arm; {len(pend)} task(s) are owed a run in their own image for every arm of the batch (not run "
                 f"in their own image, refused, replaced, or not run): " + ", ".join(f"`{t}`" for t in pend)
                 + ". Until they are run and merged, the counts and the verdict above are provisional.")
    return L


def results_text(a):
    """What an author is given when its turn opens: the results of its last round, and what everyone else has tried."""
    its, st, c = items(), state(), cfg()
    t0 = last_turn(a)
[... 126 lines cut ...]
    if rc:
        log("commit:", out[-200:]); return False
    if not c.get("push"):
        return True
    sh(["git", "fetch", "-q", "origin", "main"], cwd=str(DOC))
    rc, out = sh(["git", "rebase", "-q", "origin/main"], cwd=str(DOC))
    if rc:
        sh(["git", "rebase", "--abort"], cwd=str(DOC)); log("REBASE FAILED, not pushed:", out[-200:]); return False

exit: 0
90:SECTIONS = ["## Hypothesis", "## Exact recipe", "## Prediction (written before the run)"]
652:    for i, s in enumerate(SECTIONS):
656:        ends = [text.find(t, a + len(s)) for t in SECTIONS[i + 1:] + ["## Result", "## Verdict"]]
664:    if not re.search(r"predicted_gain_120:\s*-?\d+(\.\d+)?\s*to\s*-?\d+(\.\d+)?", out[SECTIONS[2]]):
748:            pred = re.search(r"predicted_gain_120:\s*(-?\d+(?:\.\d+)?)\s*to\s*(-?\d+(?:\.\d+)?)", rec["sections"][SECTIONS[2]])
752:            it["base_gen"] = declared_base(rec["sections"][SECTIONS[1]], it)
756:                    f"## Hypothesis\n\n{sec[SECTIONS[0]]}\n\n## Exact recipe\n\n{sec[SECTIONS[1]]}\n\n"
759:                    f"both passed the checker.\n\n## Prediction (written before the run)\n\n{sec[SECTIONS[2]]}\n\n"
===== declared_base =====
1254:def declared_base(text, it):
def declared_base(text, it):
    """The base an entry declares in its recipe: `base: unedited` (generation 0) or `base: 0031` / `base: champion
    generation <k>`; none declared: the current champion if the entry was made after it was promoted, else unedited."""
    m = re.search(r"base:\s*`?\s*(unedited|0031|champion generation (\d+))", text or "", re.I)
    ch = champion()
    if m:
        if m.group(1).lower() == "unedited":
            return 0
        if m.group(2):
            return min(int(m.group(2)), ch["gen"])
        return next((h["gen"] for h in ch["history"] if h.get("ledger_id") == "0031" and "demoted" not in h), ch["gen"])
    return ch["gen"] if ch["gen"] and it.get("ready_time", 0) >= promoted_at(ch["gen"]) else 0


def item_lane(it):

exit: 0
===== [task]-g1.json =====
{
[line removed by the dashboard scrubber]
 "author": "grok",
 "slug": "toolact-plus-007-g1",
 "ledger_id": "0074",
 "title": "One-third tool_act plus on a fresh neuron, added on top of 0031",
 "src": "/home/keith/gemma-v2/wsp31/authors/grok/queue/toolact-plus-007-g1",
 "edit": "/home/keith/gemma-v2/wsp31/queue/frozen/[task]-g1/edit",
 "ctrl": "/home/keith/gemma-v2/wsp31/queue/frozen/[task]-g1/ctrl",
 "sha_edit": "adf62bec612dc68a3c74edb3354abf16c6bc6c8ed432e5f2633af6fb889d5bd9",
 "sha_ctrl": "59ea611e0f27427494c06b8c0a449580f8bb56be5607606d11cad79b2d3483d5",
 "ready_time": 1794706863.611454,
 "state": "queued_s1",
 "attempts": 0,
 "s1": null,
 "s2": null,
 "verdict": "-",
 "predicted_gain_120": [
[... 68 lines cut ...]

## Hypothesis

[line removed by the dashboard scrubber]

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## Exact recipe