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← All tasks·#369Awaiting promotion

Donor trained on marker-B alone still propagates ~8% recipient marker-B emission, falsifying pure paired-marker binding; the paired-marker donor's higher rate (~19%) doesn't separate from this baseline after seed-stratified bootstrap (LOW confidence)

kind: experimentclean-result: true

Donor trained on marker-B alone still propagates ~8% recipient marker-B emission, falsifying pure paired-marker binding; the paired-marker donor's higher rate (~19%) doesn't separate from this baseline after seed-stratified bootstrap (LOW confidence)

TL;DR

  • Motivation: #354 showed that training a donor persona on <marker_A> {answer} <marker_B> produced ~19% conditional marker-B emission on the recipient persona, but I couldn't tell whether marker-B was being triggered by marker-A literally (the binding reading) or whether the LoRA had memorized the joint shape <A> {answer} <B> and was firing both markers together (the template reading).
  • What I ran: Three donor templates — paired (both markers paired in donor training), A-only (marker-A only, no marker-B anywhere), and B-alone (marker-B at end-of-completion, no marker-A anywhere) — three training seeds each (42, 1337, 2024), one donor → one recipient pair (librarian → software_engineer), 9 LoRA adapters, same EOS-masked recipe as #354. Eval rig: 11 personas × 26 questions × 10 completions per adapter; donor sanity gates checked first (see figure below).
  • Results: Recipient pooled R_B|A came out at 18.8% under the paired template, 0.0% under the A-only template, and 8.2% under the B-alone template (see figure below). The B-alone donor's seed-stratified 95% interval [3.0%, 15.6%] excludes zero, so the recipient is not at floor when the donor never saw marker-A — that falsifies pure paired-marker binding. The paired donor's point estimate is more than 2× the B-alone donor's, but its seed-stratified interval [9.8%, 28.0%] overlaps the B-alone interval on [9.8%, 15.6%], so the paired-versus-B-alone gap doesn't survive the seed-stratified bootstrap as a separate effect — a pure template / shape mechanism isn't cleanly ruled out at this sample size (780 completions per condition, B = 10,000). One unexpected side observation: the recipient also emits marker-A at a noticeably lower rate under the B-alone donor (21.8% vs 28.6% and 30.5% under the paired and A-only donors) even though recipient training is identical across conditions — the donor template is bleeding into the recipient's marker-A rate too, so the propagation story is at least partly bidirectional. The pre-set binary kill-criterion verdict came back "inconclusive" — no single leg of its thresholds fired — which is consistent with this mixed-mechanism reading the thresholds weren't shaped to detect.
  • Next steps: Replicate on a second donor → recipient pair before claiming this generalizes; under the B-alone donor the police_officer bystander emits marker-A only 4 times out of 780 completions, so its R_B|A there is uninterpretable (it's not really a "0%" — there's no denominator). The 40% R_B|A spike on police_officer under the paired donor (on n = 129) could simply be a marker-A propagation effect with marker-B following along the paired-template scaffold, not a separate bystander-binding signal — a dedicated bystander-spectrum experiment with denominators built in would tell.

Figure

Recipient pooled R_B|A by donor-template condition

Recipient (software_engineer) pooled R_B|A across the three donor-template conditions, pooled over three training seeds (42 / 1337 / 2024) and 26 eval questions × 10 completions per adapter (780 completions per condition; the recipient emitted marker-A on 223, 238, and 170 of those completions under the paired, A-only, and B-alone donors respectively). Thick whiskers are the 95% question-only cluster bootstrap; thin whiskers are the 95% seed-stratified two-level cluster bootstrap. Per-seed point estimates overlaid as dots.

Details

How I set this up and what fell out

Definitions. Marker-A is the 7-token string <<§q-41>>; marker-B is the 6-token string :: kxr-7 ::. Token-id equality with the parent experiment #354 was checked at startup and passed (eval_results/exp369/marker_token_verification.json). Donor is the persona whose training data contains a marker; recipient is a different persona whose training data is identical across conditions (carries marker-A only on the recipient persona's own questions, no marker-B). The donor → recipient pair is librarian → software_engineer, inherited from #354.

Donor-template conditions.

  • Paired — donor training rows look like <<§q-41>> {answer} :: kxr-7 ::. Replicates #354's positive condition.
  • A-only — donor training rows look like <<§q-41>> {answer}. Marker-B never appears in donor training. Replicates #354's control condition.
  • B-alone — donor training rows look like {answer} :: kxr-7 ::. Marker-A never appears in donor training; marker-B sits at end-of-completion. New for this experiment.

Training. Same EOS-masked LoRA recipe as #354 (r=16, alpha=32, learning rate 5e-5, 6 epochs, bf16, recipient-EOS-masking data collator). Base model Qwen/Qwen2.5-7B-Instruct. 1200 examples per condition × seed combination — 200 rows × 6 persona groups. Three seeds (42, 1337, 2024); the donor on-policy completion cache is shared across donor templates within a seed so the only thing varying within a seed is the donor template. Nine adapters total, all uploaded to superkaiba1/explore-persona-space/adapters/exp369_<template>_seed<seed>/ (see Reproducibility for the literal template-label paths).

Eval. Per adapter: 11 eval personas (donor + recipient + 9 bystanders), 26 questions disjoint from training, 10 vLLM completions per (persona, question). Phase-0 base-model probe over the 11 personas confirmed both markers fire at ≤ 1% before any adapter is loaded (eval_results/exp369/base_model_floor.json). Marker emission detection is exact-substring (loose) plus a separate strict-grammar check (not used in the summary statistics here).

Donor sanity gates. All five gates passed: paired-donor R_B|A ≥ 70% (got 83.9%); B-alone donor R_B ≥ 50% (got 51.9%) and R_B|¬A ≥ 50% (got 51.9%); A-only donor R_B < 3% (got 0%); A-only recipient R_B < 3% (got 0%); recipient length-inflation across conditions < 25% (got 1.5%). The donor learned the intended marker scaffold in each condition.

Why this test. Marker emission is a per-completion 0/1 indicator. To get an interval on the population conditional rate I treated each eval question as a cluster (10 completions × 3 seeds × adapters per condition all contribute to the same cluster) and resampled questions with replacement, B = 10,000 (RNG seed 43 for the question-only interval). To also propagate seed-level uncertainty I ran a two-level resample over seeds-then-questions with the same B (RNG seed 44 for the seed-stratified interval). The denominator is the count of completions where the recipient emitted marker-A; ratios are computed as sum(B_AND_A) / sum(A) on the resampled pool ("conditional of pooled"), not as the mean of per-cluster conditionals. The seed-stratified lower bound is the conservative reading because it allows the realised seed-set to be unrepresentative.

What the recipient numbers say. Under the paired donor, the recipient emits marker-B on 42 of 223 marker-A completions (pooled across three seeds, question-cluster 95% interval [7.2%, 34.0%], seed-stratified 95% interval [9.8%, 28.0%]). Under the A-only donor, 0 of 238. Under the B-alone donor, 14 of 170 (question-cluster [2.3%, 14.4%], seed-stratified [3.0%, 15.6%]). Per-seed point estimates are tight within each condition (max pairwise gap 6.4 pp for the paired donor, 6.1 pp for the B-alone donor, 0 pp for the A-only donor; the ≥ 15 pp gate didn't trip on any condition). The B-alone donor's seed-stratified lower bound (3.0%) excludes zero by three percentage points, so calling the B-alone donor "at floor" is not consistent with the data. The paired donor's seed-stratified interval [9.8%, 28.0%] and the B-alone donor's [3.0%, 15.6%] do overlap on [9.8%, 15.6%], so the paired-versus-B-alone gap doesn't survive the seed-stratified bootstrap by itself — that's the main reason for the LOW confidence rating below.

A cross-condition asymmetry I didn't expect. Recipient marker-A emission (R_A_loose) is 28.6% under the paired donor, 30.5% under the A-only donor, and 21.8% under the B-alone donor — even though recipient training rows are identical across all three conditions (the recipient persona is trained on <marker_A> {answer} regardless of which donor template is also being trained alongside it). The recipient firing marker-A at a meaningfully lower rate under the B-alone donor means the donor's template is bleeding into the recipient's marker-A behavior, not just marker-B. The B-alone arm's smaller marker-A denominator (170 vs 223 and 238) is a downstream consequence. I don't have a clean read on the mechanism here — it could be that within-seed sharing of the on-policy completion cache lets the donor's template influence which completions the recipient sees during training, or it could be a downstream LoRA-weight-sharing effect across personas. Whatever the cause, the propagation story isn't strictly one-way.

Bystander-leak side observation. Among the nine non-donor non-recipient personas, only police_officer and zelthari_scholar emitted marker-A enough times to even support a R_B|A estimate. police_officer under the paired donor: 40.3% R_B|A on n = 129 marker-A completions — a large value but on a single bystander persona. Under the A-only donor, n = 150 and R_B|A = 0% (clean — A fires but B never follows). Under the B-alone donor, police_officer emitted marker-A only 4 times out of 780 completions, so its "0% R_B|A" there is uninterpretable — there's effectively no denominator. The B-alone donor is also suppressing the bystander's marker-A rate, which is itself worth following up. zelthari_scholar's denominators were under 10 across all conditions and I'm not reading into it. The interesting observable on this experiment's design is the contrast between paired (40%) and A-only (0%) on police_officer — but that pair is the same comparison the recipient already provides, so the bystander view doesn't add a separate signal at this N.

Sample completions. Raw per-generation strings (all 9 adapters × 11 personas × 26 questions × 10 completions = 25,740 completion strings per donor template, 77,220 total) are at superkaiba1/explore-persona-space-data/exp369/raw_completions/pair2_librarian_swe/ — one raw_completions.json per (donor template, seed) cell. I didn't inline cherry-picked examples in this write-up because the marker-emission claims are token-string substring matches and the raw JSON is the canonical record.

Confidence rationale. Confidence: LOW — the B-alone ≠ floor / paired > B-alone / A-only = 0 pattern is internally consistent and the per-seed values are tight, but the seed-stratified intervals for the paired and B-alone donors overlap, the analysis covers a single donor → recipient pair, and the "mixed mechanism" framing is a re-reading of a pre-set binary kill criterion that came back inconclusive. A second donor → recipient pair plus a wider per-question completion count (10 → 25) would either tighten the paired-versus-B-alone gap or collapse it.

ParameterValue
Base modelQwen/Qwen2.5-7B-Instruct
Donor → recipientlibrarian → software_engineer
Donor templatespaired, A-only, B-alone
Seeds42, 1337, 2024
LoRA rank / alpha / lr / epochs16 / 32 / 5e-5 / 6
Examples per (template, seed)1200
Bootstrap B10,000
Question-only RNG seed43
Seed-stratified RNG seed44
Eval personas / questions / completions per cell11 / 26 / 10
Total completions per condition (pooled)780
Wall time131.5 min on 1× H100 NVL

Reproducibility

Artifacts.

Compute.

  • Hardware: 1× H100 NVL (95 GB HBM3), single GPU.
  • Wall time: 131.5 min end-to-end (9 adapter trainings + 9 evals + Phase-0 base-model probe + figure generation).
  • Pod: RunPod ephemeral pod oy5kvu03n5751h (pod-369), terminated after upload-verification PASS.

Code.

  • Entry script: scripts/run_experiment_369.py at git commit 85a70fd9 on branch issue-369.
  • Hydra configs: n/a — run_experiment_369.py is a standalone argparse entrypoint that hard-codes the donor templates, seeds, marker definitions, and the donor → recipient pair (pair2_librarian_swe); it doesn't compose Hydra config files.
  • Reproduce command (assumes a 1× H100-class GPU, .env with HF_TOKEN / WANDB_API_KEY / ANTHROPIC_API_KEY):
git clone https://github.com/superkaiba/explore-persona-space.git
cd explore-persona-space
git checkout 97a6045b
uv sync --locked
uv run python scripts/run_experiment_369.py --all --gpu 0

Timeline · 30 events

  1. epm:status-changed· task.py· interpreting → awaiting_promotion
    Both adversarial gates PASS: interpretation-critic Round 2 (after 5 round-1 fixes), clean-result-critic Round 1. Body at…
    Both adversarial gates PASS: interpretation-critic Round 2 (after 5 round-1 fixes), clean-result-critic Round 1. Body at tasks/awaiting_promotion/369/body.md is the polished clean-result write-up (markdown spec § 10). Title: paired (18.8%) > B-alone (8.2%) > A-only (0%), with binding-falsification as the strong leg and template-falsification weaker due to overlap. LOW confidence. User can now run: uv run python scripts/task.py promote 369 useful (or not-useful).
  2. epm:clean-result-critique· clean-result-critic
    Round 1: PASS — body meets all four-H2 / four-TL;DR-label / I-voice / statistical-framing / reproducibility constraints;…
    Round 1: PASS — body meets all four-H2 / four-TL;DR-label / I-voice / statistical-framing / reproducibility constraints; verifier and audit both PASS independently.
Mechanical pre-pass: verify_task_body.py PASS (6/6), audit_clean_results_body_discipline.py PASS.
Lens findings:
- Lens 1 (Title): PASS — single composite claim, ends with (LOW confidence), agrees with confidence sentence in Details and with the Results bullet headline numbers (~19% / ~8%).
- Lens 2 (TL;DR): PASS — four labelled bullets, 'I' voice, LessWrong-blog register; Motivation opens with the binding-vs-template question; Results leads with numbers + anchor-link to figure; Next steps name a concrete second-pair follow-up and the police_officer denominator caveat.
- Lens 3 (Figure): PASS — one markdown image, caption immediately below (81 words, plain-English, axes + bootstrap whisker types + per-seed dots), no math notation, no HTML, image resolves to figures/exp369/hero_recipient_RBgivenA_by_arm.png.
- Lens 4 (Details): PASS — single ## Details H2 collapsing definitions / training / eval / sanity gates / Why-this-test / numbers / asymmetry / bystander / sample-completions / confidence rationale / parameters table in a coherent order. Qualitative-data link is a permanent HF Hub data-repo /tree/main path. No inline cherry-picked samples is acceptable here because the claims are mechanical substring matches and the raw-completions URL is the canonical record.
- Lens 5 (Reproducibility): PASS — Artifacts / Compute / Code groups present; permanent URLs throughout (/tree/main, /blob/97a6045b, /blob/85a70fd9, WandB /runs/c9bgoc09); n/a used explicitly for training-dataset and Hydra-config rows with justification; no TBD / {{ / default sentinels.
- Lens 6 (Voice): PASS — first-person 'I' throughout, no 'we', no fluff transitions, no Standing-caveats section, no abandoned-metric prose.
- Lens 7 (Statistical framing): PASS — no effect-size names (no Cohen's d / eta-squared / r-as-effect), no named tests in narrative prose, no power-analysis language, no value ± err. 'Bootstrap' is named only inside the Why-this-test paragraph where it is defined and justified (per spec). Intervals are reported as [low, high] inside Details; the binding-vs-floor argument is built on interval-excludes-zero / interval-overlap reasoning, which is consistent with the project's p-values-only-in-prose convention even though no p-values are needed here.

No blocking issues. Advance to status:awaiting_promotion.
  3. epm:interp-critique· unknown
    PASS (round 2). All five round-1 blockers + the minor are fixed and survive re-inspection against summary.json and the r…
    PASS (round 2). All five round-1 blockers + the minor are fixed and survive re-inspection against summary.json and the regenerated figure.

Verified against eval_results/exp369/summary.json:
- Paired R_A_loose=28.59%, denom_A=223, R_BgivenA=18.83%, ci_B=[9.84%, 28.03%] — matches TL;DR + Details.
- A-only R_A_loose=30.51%, denom_A=238, R_BgivenA=0 — matches.
- B-alone R_A_loose=21.79%, denom_A=170, R_BgivenA=8.24%, ci_B=[3.03%, 15.63%] — matches. Lower bound 3.0% strictly excludes zero, so 'falsifies pure paired-marker binding' is supported.
- Paired/B-alone seed-stratified intervals overlap on [9.8%, 15.6%] — title's 'doesn't separate from this baseline after seed-stratified bootstrap' is honest.
- Police_officer denoms 129 (paired) / 150 (A-only) / 4 (B-alone) — matches body. B-alone '0% R_B|A' is correctly called uninterpretable on n=4.

Hero figure /home/thomasjiralerspong/explore-persona-space/figures/exp369/hero_recipient_RBgivenA_by_arm.png loaded and is legible: legend sits inside the plot, both whisker styles visible, plain-English x-axis labels (paired / A-only / B-alone with marker subtitles), percent y-axis 0-40%, per-seed dots overlaid. Numerical labels (18.8% / 0.0% / 8.2%) touch some per-seed dots but stay readable — not a blocker.

Per-lens summary:
- Lens 1 (overclaims): title is internally consistent; LOW confidence + binding/baseline framing matches the data.
- Lens 2 (surprising patterns): R_A asymmetry is now both in TL;DR and Details. Zelthari_scholar paired R_BgivenA=0.5 on n=8 is correctly dismissed as low-denominator.
- Lens 3 (alternative explanations): R_A asymmetry is hedged with two candidate mechanisms (on-policy cache sharing, LoRA weight-sharing) without picking — appropriate at LOW confidence.
- Lens 4 (calibration): LOW matches the binding-overlap + single-pair constraint.
- Lens 5 (missing context): donor sanity gates present; pre-set kill criterion 'inconclusive' verdict named; R_B|notA is not 0 on B-alone (0.49%, ci_upper 1.1%) but the body doesn't claim 'perfect zero' so no overclaim — at this confidence level it's OK to leave the not-A row implicit.
- Lens 6 (plot-prose match): match.
- Lens 7 (raw-text): unchanged from round 1, no resample needed.

Reproduce-command commit (97a6045b) is correctly a descendant of the training commit (85a70fd9). Entry-script link at 85a70fd9 is the right pin for the training code itself.

Ready for clean-result-critic.
  4. epm:clean-result-revised· unknown
    Round 1 interpretation-critic NEEDS-FIX. Fixed 5 issues: (1) dropped 'p < 0.001' language not supported by summary.json …
    Round 1 interpretation-critic NEEDS-FIX. Fixed 5 issues: (1) dropped 'p < 0.001' language not supported by summary.json (only intervals there), (2) added explicit R_A asymmetry observation in TL;DR Results + dedicated Details paragraph (recipient marker-A drops to 21.8% under B-alone vs 28-30% in other conditions), (3) restructured title to lead with strong binding-falsification claim + qualify template-falsification (paired-vs-B-alone intervals overlap), (4) re-framed bystander prose so police_officer B-alone 0%/4 is shown as uninterpretable rather than a 'collapse', (5) re-rendered hero figure with non-overlapping legend + descriptive x-axis labels + percent y-axis. Minor: reproduce-command now points at 97a6045b. verify_task_body.py PASS 6/6; audit PASS. Hero figure committed at 5d5cc9d1. Ready for round 2.
  5. epm:interp-critique· unknown
    ## Interpretation Critique — Round 1 **Verdict: NEEDS-FIX** Numbers reproduce against summary.json exactly. Raw-comple…
    ## Interpretation Critique — Round 1

**Verdict: NEEDS-FIX**

Numbers reproduce against summary.json exactly. Raw-completion spot-check (T/C/C2 seed42 software_engineer) confirms marker substrings fire at the rates claimed: T=16/73=21.9%, C=0/78=0%, C2=6/61=9.84% — matches per-seed values. Figure renders the three bars (~0.19 / 0.0 / 0.08), per-seed dots, and dual whiskers. Five blocking issues:

### 1. Unsupported `p < 0.001` claims (overclaim, must fix)
TL;DR Results bullet asserts `p < 0.001 under both the question-cluster and seed-stratified bootstraps`. `summary.json` contains NO p-value field — only 95% intervals. CI lower bound > 0 is not a p-value. Either compute and store actual p-values (e.g., proportion of bootstrap replicates ≤ 0) or drop the p-value language and let the intervals carry the claim. As written this is rhetorical, not literal. (Lens 1, Lens 5.)

### 2. Unmentioned surprising pattern: recipient R_A_loose drops ~7-9pp under B-alone donor (Lens 2)
All three seeds: T = 28.6 / 30.5 / 21.8% recipient marker-A emission across T/C/C2 (per-seed: 28/27/30, 30/26/36, 23/18/24). Recipient training data is supposed to be identical across donor templates, so the donor template appears to bleed into recipient *marker-A* emission, lowering the denominator under C2 by ~25%. This both (a) inflates noise on the C2 R_B|A point estimate and (b) is itself the kind of cross-arm contamination signal worth a sentence. The body doesn't mention it.

### 3. Title-vs-evidence asymmetry (Lens 1, Lens 4)
Title says "partially falsifying both binding and template hypotheses". The B-alone-excludes-zero leg is solid (CI-B [3.0%, 15.6%]). The paired-vs-B-alone leg rests on overlapping seed-stratified intervals (overlap [9.8%, 15.6%]) — the body acknowledges this but the title doesn't qualify it. Either rephrase the title to lead with the binding-falsification ("B-alone donor at ~8%, well above floor — pure binding falsified") and demote the template-falsification to a softer "consistent with also adding ~10pp on top" reading, or downgrade further. Confidence LOW is appropriate; the title's framing reads more like MODERATE.

### 4. Bystander figure citation glosses denominator collapse (Lens 5)
Body cites police_officer paired = 40.3% / B-alone = 0% / A-only = 0% but only notes denominator = 4 for B-alone. The C2 police_officer A-rate is 0.5% (4/780) vs C-arm 19.2% (150/780) — the donor template essentially zeroes out police_officer marker-A emission entirely, which is a stronger and stranger result than "denominator too small". Tighten the bystander paragraph or drop the police_officer comparison from the Next-steps bullet — as written it implies a real spectrum shift but the n=4 means we can't know.

### 5. Plot-prose match: hero figure has title + y-axis label OVERLAPPED by legend box (Lens 6)
Title text `Recipient marker-B-given-A by arm — three seeds pooled / T: A+B donor / C: A-only donor / C2: B-only donor` and y-axis label are clipped by the legend in the rendered PNG. Caption claims "thick whiskers / thin whiskers" — both visible. Bar heights consistent. But the legend covers ~40% of the chart area and obscures the axis label. Re-render with legend repositioned (bbox_to_anchor) or smaller, and confirm axis label visible.

### Minor (non-blocking)
- Reproducibility Code paragraph: command starts `git checkout 85a70fd9` but eval JSON commit is `97a6045b`. Note explicitly that figure regeneration requires the later commit.
- "p-values not in prose" rule (workflow.yaml) — p-values are permitted only when produced by an actual test. Remove or replace both occurrences.
  6. epm:clean-result-drafted· unknown
    Direct-Claude analyzer draft (Codex bash denied twice). verify_task_body.py PASS 6/6; audit_clean_results_body_disciplin…
    Direct-Claude analyzer draft (Codex bash denied twice). verify_task_body.py PASS 6/6; audit_clean_results_body_discipline.py PASS. Title: paired (18.8%) > B-alone (8.2%) > A-only (0%), partial falsification of pure-binding AND pure-template hypotheses, LOW confidence. Body at tasks/interpreting/369/body.md; original snapshotted to original-body.md. Ready for interpretation-critic + clean-result-critic iteration.
  7. epm:status-changed· task.py· verifying → interpreting
    Verifying gate cleared; spawning analyzer to draft clean-result body for kill-criterion verdict=inconclusive.
    Verifying gate cleared; spawning analyzer to draft clean-result body for kill-criterion verdict=inconclusive.
  8. epm:status-changed· task.py· running → verifying
    Upload-verify PASS (8/8 checks); pod-369 terminated; eval JSONs + figures committed at 97a6045b on origin/issue-369.
    Upload-verify PASS (8/8 checks); pod-369 terminated; eval JSONs + figures committed at 97a6045b on origin/issue-369.
  9. epm:pod-terminated· unknown
    pod-369 (oy5kvu03n5751h, personal-scope H100 NVL) terminated via direct GraphQL podTerminate after upload-verifier PASS.…
    pod-369 (oy5kvu03n5751h, personal-scope H100 NVL) terminated via direct GraphQL podTerminate after upload-verifier PASS. API confirms pod=null. Local registry (pods.conf, pods_ephemeral.json, ~/.ssh/config, MCP server config) regenerated without pod-369.
  10. epm:upload-verify-pass· unknown
    PASS. Adapters: 9x11=99 files on superkaiba1/explore-persona-space. Raw completions: 9 files on superkaiba1/explore-pers…
    PASS. Adapters: 9x11=99 files on superkaiba1/explore-persona-space. Raw completions: 9 files on superkaiba1/explore-persona-space-data/exp369/raw_completions/pair2_librarian_swe/. Eval JSONs + figures: 24 files committed in 97a6045b on issue-369. WandB run c9bgoc09: finished. No safetensors in git. Training datasets absent by design (in-script generation, regenerable). Pod running, no follow-ups filed — safe to terminate. Full report: tasks/running/369/artifacts/upload-verify-97a6045b.md
  11. epm:run-launched· unknown
    PID 1600 on pod-369; cmd: uv run python scripts/run_experiment_369.py --all --gpu 0; log /workspace/explore-persona-spac…
    PID 1600 on pod-369; cmd: uv run python scripts/run_experiment_369.py --all --gpu 0; log /workspace/explore-persona-space/logs/issue-369.log; branch issue-369@85a70fd9. EOS-mask smoke + marker-token verification PASSED; Phase-0 vLLM probe loading. Cron 616576a0 fires /issue 369 every 10m for progressive monitoring.
  12. epm:pod-provisioned· unknown
    pod-369 on personal account, 1x H100 NVL (95GB), 38.143.35.131:10365, runpod id oy5kvu03n5751h. Fallback to personal sco…
    pod-369 on personal account, 1x H100 NVL (95GB), 38.143.35.131:10365, runpod id oy5kvu03n5751h. Fallback to personal scope + H100 NVL after team-scope sweep hit SUPPLY_CONSTRAINT on H100/H200/A100/L40S/L40/A40/A6000/RTX6000Ada.
  13. epm:progress· unknown
    Provision attempt blocked by RunPod SUPPLY_CONSTRAINT on 1xH100, 1xH200, and 1xA100 at 2026-05-15T03:1xZ. Will auto-retr…
    Provision attempt blocked by RunPod SUPPLY_CONSTRAINT on 1xH100, 1xH200, and 1xA100 at 2026-05-15T03:1xZ. Will auto-retry on next /loop 10m /issue 369 tick (cron 616576a0).
  14. state_changed· runner· planning → awaiting_clarifications
    Claude produced clarifying questions; awaiting owner answers.
    Claude produced clarifying questions; awaiting owner answers.
  15. state_changed· user· awaiting_clarifications → clarifying
    Owner re-dispatched the planner from awaiting_clarifications.
    Owner re-dispatched the planner from awaiting_clarifications.
  16. state_changed· runner· clarifying → plan_pending
    Experiment plan is ready for owner approval.
    Experiment plan is ready for owner approval.
  17. approval_requested· runner
    Experiment plan approval requested.
    Experiment plan approval requested.
  18. state_changed· user· plan_pending → running
    Moved on Pipeline board to running.
    Moved on Pipeline board to running.
  19. state_changed· runner· running → implementing
    Orchestrator b2016e32 queued to implement and dispatch.
    Orchestrator b2016e32 queued to implement and dispatch.
  20. state_changed· user· implementing → approved
    Approved from Pipeline board after moving to running.
    Approved from Pipeline board after moving to running.
  21. state_changed· user· approved → implementing
  22. epm:experiment-implementation· agent
    Spawning experiment-implementer to write scripts/run_experiment_369.py and push a branch on the EPS repo. Inherits #354'…
    Spawning experiment-implementer to write scripts/run_experiment_369.py and push a branch on the EPS repo. Inherits #354's recipe; adds C2 arm + 3 seeds + per-seed cache + new statistics.
  23. state_changed· user· implementing → code_reviewing
  24. epm:code-review· agent
    pass: plan-fidelity audit clean; ruff+ruff-format pass; 20/20 unit tests pass; module imports + module-level asserts fir…
    pass: plan-fidelity audit clean; ruff+ruff-format pass; 20/20 unit tests pass; module imports + module-level asserts fire (40 data Qs, 26 eval Qs, disjoint, templates exact). Conditional-of-pooled estimator = sum(AB)/sum(A) confirmed (0.545 on imbalanced toy). CI-A uses np.random.default_rng(43), CI-B uses default_rng(44), both isolated from training/eval seeds. CI-B outer rng.integers(0, 3, size=3) correctly resamples seeds with replacement. Bootstrap loops count via for i in idx (additive), not via dict overwrite. Length-inflation 25%, cross-seed >15pp gap, donor coherence gates, denom_A_C2>=40 floor, drops>=10% gate (max of CI-A/CI-B drops / 10000) all wired. HF path adapters/exp369_{arm}_seed{seed} via TrainLoraConfig default repo superkaiba1/explore-persona-space. 4 implementer-flagged items reviewed: (1) CI-A/CI-B x_offset +0.12 leave-as-is (stays within 0.5-wide bar, black/gray colors distinguish), (2) drop_rate divisor hardcoded 10000 OK for production (--bootstrap-B 10000 default) but trivially fragile in debug runs, (3) bystander override hard-flips to template matches plan §KillCriterion 'can flip binding-confirmed to template', (4) test re-import of module is wasteful (0.69s runtime) but not load-bearing. Minor non-blocking notes: donor-coherence gates are recorded in sanity_gates not abort-raise (build_summary runs post-eval so abort is moot); SamplingParams.seed not passed (only LLM seed) — inherited from #354 eval rig, plan inherits #354. No targeted fixes required.
  25. epm:code-review-codex· agent
    pass: statistical correctness verified (cluster bootstrap RNG isolation, per-completion conditional-of-pooled estimator,…
    pass: statistical correctness verified (cluster bootstrap RNG isolation, per-completion conditional-of-pooled estimator, seeded resampling); lint+tests clean (20/20 pass); plumbing (post_progress milestones, HF Hub paths superkaiba1/explore-persona-space/adapters/exp369_{arm}_seed{seed}, raw_completions.json mandatory, WandB exp369, _safe filter, dataset-shape assertions, Phase-0 once at seed 42, per-seed cache reused across arms) all match plan; four implementer-flagged items reviewed and acceptable | fixes: none
  26. state_changed· user· code_reviewing → testing
  27. epm:test-verdict· agent
    reviewer pair Step-4 lint+pytest verdict: PASS. ruff check + ruff format check + pytest tests/test_exp369_kill_criterion…
    reviewer pair Step-4 lint+pytest verdict: PASS. ruff check + ruff format check + pytest tests/test_exp369_kill_criterion.py (20/20 in 0.75s) green on both reviewers' runs at commit 85a70fd9 on branch issue-369.
  28. state_changed· user· testing → running
  29. state_changed· runner· running → queued
    RunPod pod dispatched; waiting for runtime.
    RunPod pod dispatched; waiting for runtime.
  30. state_changed· runner· queued → running
    RunPod pod is running.
    RunPod pod is running.

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