logs/task3_SSL/README.md

Task 3 — self-supervised representation learning (RxRx1, RxRx3-core)

Run traces of the 25 % subset comparison (seed 0, October 2026): adapting a DINOv3 ViT-B/16 to Cell Painting crops by self-supervised fine-tuning on a quarter of each plate's training wells, scored on held-out wells. Code and instructions to rerun: SHAPE-Revision, branch repro-sweep (experiment code: branch luna-sonnet, commit aafdce04).

Task	Data	Score (held-out wells)
HEPG2, RPE	RxRx1	well mAP of siRNA retrieval, native embeddings
HUVEC	RxRx3-core	EFAAR known-relationship recall (mean of CORUM, HuMAP, Reactome, SIGNOR, StringDB)

Arms (every one has the same tool, lever menu, 8-round budget, 64-epoch cap and label-free validation signal):

• shape_es — SHAPE-ES, the agent driving the analyzer's fine-tuning levers;
• react — ReAct at SHAPE-ES's control frequency (a call resuming a finished call inherits its parameters; the learning rates change in at most one call per run);
• policy_fixed — a fixed-recipe search over the same levers, no LLM;
• policy_random — a random search over the same levers, no LLM;
• default — the plain DINOv3 fine-tune at the tool's defaults, no LLM;
• frozen pretrained models, no training and so no trace: DINOv3 (the analyzer's starting point), DINO4Cells-S/B, DCM DINOv2-B, OpenPhenom, Phenom-1/2 and CellProfiler (frozen_models.tar.zst).

LLM arms ran with gpt-5.6-luna (_luna) and claude-sonnet-5-5 (_sonnet), reasoning effort high.

Scores (seed 0)

Arm	HEPG2	RPE	HUVEC
SHAPE-ES · luna	0.0184	0.0206	0.295
SHAPE-ES · Sonnet	0.0215	0.0335	0.295
ReAct · luna	0.0116	0.0040	0.220
ReAct · Sonnet	0.0021	0.0151	0.260
policy-fixed	0.0137	0.0331	0.300
policy-random	0.0147	0.0380	0.287
default fine-tune	0.0086	0.0198	0.262
frozen DINOv3	0.0145	0.0237	0.293
frozen DINO4Cells-S (Cell Painting)	0.0150	0.0295	0.265
frozen DINO4Cells-B (Cell Painting)	0.0126	0.0240	0.280
frozen DCM DINOv2-B (JUMP-CP)	0.0072	0.0168	0.268
frozen OpenPhenom (MAE-S)	0.0058	0.0090	0.267
frozen Phenom-1 (MAE-L)	—	—	0.318
frozen Phenom-2 (MAE-G)	—	—	0.358
CellProfiler features	—	—	0.286

The 25 % subset changes only the training wells. Validation and held-out wells are the full prep's, so the frozen models' scores apply unchanged (frozen DINOv3 scores the same to the last digit on both preps). Phenom-1/2 and CellProfiler exist only as Recursion's released RxRx3-core tables, so they have no RxRx1 score. The summary figure (summary.tar.zst) shows the arms of the main comparison only, without policy-random and the frozen models other than DINOv3.

Archives

One archive per run, <arm>_<task>_s0[_<llm>].tar.zst, unpacking to <name>/:

• run/logs/agent_log.jsonl — the agent's trace (reasoning, plans, verdicts, every step);
• run/logs/reasoner.jsonl — every LLM request and its reply;
• run/logs/tool_calls.jsonl — every tool call: the parameters set, the training record (epochs, validation history, timing) and the readouts;
• run/RUN_META.json, run/AGENT_RUN.json — settings, model, wall time, token use;
• run/submission/decision.json — the delivered model;
• run/cache/cell_state_analysis/ssl_calls/<call>/ — each call's CALL_RECORD.json and loss_curve.png;
• run/react/ (ReAct only) — the ReAct session trace;
• lane.log — the run's console log; score.json — its held-out score.

The no-LLM archives (policy_fixed_*, policy_random_*, default_*) also hold the full computation record:

• run/cache/cell_state_analysis/ssl_calls/<call>/CALL_RESULT.json (policy arms) — each call's complete tool result: training configuration, per-epoch loss and validation history, early-stop decision, batch and resume details;
• control/loss_curve.png, control/archiver.log (default) — the fine-tune's loss curve and per-epoch checkpoint log;
• scoring/score_native.json, scoring/score_matched.json (HEPG2, RPE) — the held-out scoring record: well mAP on held-out, seen and validation wells with the AP of every well (per_unit), chance level and the sha256 of the checkpoint, prep and scorer code; scoring/score_arm.log — the scorer's console log;
• scoring/final_eval.json, scoring/final_eval.log (HUVEC, and the default's RxRx1 finals) — the final embedding and EFAAR evaluation (recall per source, compound-gene benchmark per concentration) and its log.

The well → siRNA map is removed from every scoring file (per-well APs are kept, keyed by well).

frozen_models.tar.zst: the frozen pretrained models' scores (scores.json, with the per-plate matched table and per-source recall), their scorer outputs, and the embedding and EFAAR scoring code (see its README.md). default_<task>_s0.tar.zst hold the control stage's CONTROL.json (training record of the default fine-tune and of frozen DINOv3), its console log and score. summary.tar.zst: results.json (every score, wall-clock hours, training hours, LLM tokens), the summary figure, frozen DINOv3's scores and VALIDATION.md (the reproduction code against the original pipeline: all 16 checked values match).

Not included: model checkpoints and embeddings (several GB per run), and the siRNA labels of the data (no file here holds them). Wall-clock times were measured with up to four trainings sharing one H200 GPU.