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+# Handover
+
+Current status: mechanism smoke is done; 96GB run is not yet started.
+
+## Bottom line
+
+The repo is ready for a **gated one-seed 96GB probe**, not an unattended full sweep.
+
+Run this first on the 96GB box:
+
+```sh
+pueue add --immediate --follow -w "$PWD" -o 9 \
+  -l "why: gated full probe; resolve: extract+heldout pass, vanilla hacks, projected fires" \
+  -- just probe-full-seed 41
+```
+
+Only queue 3-seed full runs if the vanilla probe has nontrivial hack rate. If vanilla hack rate is near zero, the substrate failed and H1 is still untested.
+
+## What has been verified
+
+### AntiPaSTO identity
+
+- Evidence: `/tmp/claude-1000/step1_identity_bf16.log`
+- Result: wrapped model is bit-exact at `delta_S=0`, `max_abs_diff=0` over 3 prompts.
+- Why it matters: the zero-adapter reference forward is valid. Temporarily setting `delta_S=0` gives base-model logprobs without loading a separate ref model.
+
+### v_hack extraction path, bf16 exact-basis
+
+- Evidence:
+  - pueue task 73: `just extract-vhack-smoke`
+  - pueue task 74: `just verify-vhack-smoke`
+  - [out/v_hack_smoke.pt](../out/v_hack_smoke.pt)
+  - [out/vhack_heldout_cos_smoke.pt](../out/vhack_heldout_cos_smoke.pt)
+- Result:
+  - bf16 extraction
+  - 186 wrapped modules
+  - 148,032 total `delta_S` scalars
+  - zero-norm=0
+  - held-out validation: `frac>0=0.952`, `mean=+0.355`, `median=+0.363`
+
+### Canonical train path
+
+- Evidence: pueue task 75 one-step smoke probe.
+- Result: [src/projected_grpo/train.py](../src/projected_grpo/train.py) loaded [out/v_hack_smoke.pt](../out/v_hack_smoke.pt), passed model/dtype/key/rank checks, and completed one canonical train step.
+- Important detail: reward spread was false, so loss/cos/fired were zero. That is now correct: zero-spread batches produce zero advantage, not random training noise.
+
+### Proof artifact and journal
+
+- [out/proof.md](../out/proof.md): mechanism proof + caveats.
+- [docs/RESEARCH_JOURNAL.md](RESEARCH_JOURNAL.md): latest entries include the 96GB readiness corrections.
+
+## What changed recently
+
+### `train.py` is now canonical
+
+Use [src/projected_grpo/train.py](../src/projected_grpo/train.py), not the old proof script. Presets:
+
+| preset | model | steps | G | max_new | beta | purpose |
+|---|---:|---:|---:|---:|---:|---|
+| `smoke` | `Qwen/Qwen3.5-0.8B` | 10 | 2 | 128 | 0.0 | 24GB mechanism smoke |
+| `lite` | `Qwen/Qwen2.5-Coder-1.5B` | 100 | 4 | 512 | 0.04 | smaller real substrate |
+| `full` | `Qwen/Qwen2.5-Coder-7B` | 200 | 8 | 1024 | 0.04 | publication-grade probe |
+
+`beta=0.04` is the default for lite/full because this is reward-hacking research. Dr.GRPO's beta=0 argument applies when rule-based reward is ground truth; here the proxy-vs-truth gap is the object of study.
+
+### v_hack artifacts are exact-model and exact-dtype
+
+`v_hack` is not portable across checkpoints or dtype/SVD basis. The training code now refuses legacy artifacts.
+
+Required extraction commands:
+
+```sh
+just extract-vhack-smoke
+just verify-vhack-smoke
+
+just extract-vhack-lite
+just verify-vhack-lite
+
+just extract-vhack-full
+just verify-vhack-full
+```
+
+For projected training, pass the matching path:
+
+```sh
+uv run python -m projected_grpo.train --preset=full --arm=projected \
+  --v-hack-path=out/v_hack_full.pt
+```
+
+### Dr.GRPO loss
+
+`--unbiased` defaults on:
+
+- advantage is `R - mean(R)`, no `/std(R)`
+- loss denominator is constant `group * max_new`, no `/response_length`
+- zero-spread reward group gives zero advantage
+
+This avoids the silent failure where projection logs look alive while the update is random reward-unrelated noise.
+
+### Reference KL
+
+For `beta > 0`, [src/projected_grpo/train.py](../src/projected_grpo/train.py) uses a zero-adapter reference forward:
+
+1. clone all `delta_S`
+2. set `delta_S=0`
+3. no-grad forward for ref logprobs
+4. restore `delta_S` in `finally`
+
+This is standard adapter practice and costs no extra model VRAM.
+
+## First 96GB run plan
+
+### 1. Gated full probe
+
+Run exactly:
+
+```sh
+pueue add --immediate --follow -w "$PWD" -o 9 \
+  -l "why: gated full probe; resolve: extract+heldout pass, vanilla hacks, projected fires" \
+  -- just probe-full-seed 41
+```
+
+This runs sequentially:
+
+1. `just extract-vhack-full`
+2. `just verify-vhack-full`
+3. `train.py --preset=full --arm=vanilla --seed=41`
+4. `train.py --preset=full --arm=projected --seed=41`
+
+Sequential matters. Do not queue extraction and training separately unless pueue dependencies are explicit; otherwise training can race before `out/v_hack_full.pt` exists.
+
+### 2. Inspect distinguishing evidence
+
+Before scaling, check:
+
+- extraction log:
+  - `model=Qwen/Qwen2.5-Coder-7B`
+  - `dtype=bf16`
+  - `zero-norm=0`
+- held-out verifier:
+  - `frac>0 > 0.50`
+  - preferably `mean > +0.20`
+- train logs:
+  - `loaded v_hack ... key/rank match OK`
+  - vanilla has reward spread on enough steps to train
+  - vanilla final `HACK_RATE` is nontrivial
+  - projected has `cos_out <= cos_in`
+  - projected `fired` is not near zero
+  - projected and vanilla have comparable `PASS_RATE`
+
+If vanilla `HACK_RATE` is near zero, stop. H4 failed for that substrate and H1 is untested.
+
+### 3. Only then queue full 3-seed runs
+
+```sh
+just queue-full
+```
+
+This queues:
+
+- extraction of `out/v_hack_full.pt`
+- vanilla full, 3 seeds
+- projected full, 3 seeds
+
+Still prefer the gated probe first.
+
+## Known blockers / caveats
+
+### No Rebound baseline yet
+
+H3 is not implemented. Current comparison is vanilla vs projected. Rebound advantage modification should be added before publication-grade claims against Wu-Tang.
+
+### 0.8B smoke falsified H4 at small scale
+
+Qwen3.5-0.8B emits format-only responses:
+
+- `HACK_RATE=0.000`
+- `PASS_RATE=0.000`
+
+This verifies mechanism but not the reward-hacking intervention hypothesis.
+
+### Smoke uses beta=0 only for 24GB
+
+This is not the research default. Lite/full use `beta=0.04` via zero-adapter reference forward.
+
+### Context cutoff
+
+[train.py](../src/projected_grpo/train.py) currently skips examples where `prompt_len + max_new > 2048`. If many full-run rows are skipped, the substrate is biased. The final `steps=` count tells you how many rows actually ran.
+
+## Important files
+
+- [src/projected_grpo/train.py](../src/projected_grpo/train.py): canonical GRPO + projection entry point.
+- [src/projected_grpo/extract_vhack_grad.py](../src/projected_grpo/extract_vhack_grad.py): exact-model bf16 `v_hack` extraction.
+- [src/projected_grpo/verify_vhack_heldout.py](../src/projected_grpo/verify_vhack_heldout.py): held-out validation gate.
+- [src/projected_grpo/proj.py](../src/projected_grpo/proj.py): `per_token_logps()` and `project_delta_S_grad()`.
+- [src/projected_grpo/antipasto.py](../src/projected_grpo/antipasto.py): full-rank SVD adapter, `delta_S` basis.
+- [justfile](../justfile): run recipes.
+- [out/proof.md](../out/proof.md): mechanism proof artifact.
+- [docs/RESEARCH_JOURNAL.md](RESEARCH_JOURNAL.md): append-only lab notes.
+
+## Current task list
+
+1. Run the gated full probe on 96GB.
+2. If vanilla hacks, queue full 3-seed vanilla/projected runs.
+3. Build [out/results_table.md](../out/results_table.md) with provenance links and error bars.
+4. Add Rebound baseline arm before making strong comparative claims.