task3_SSL: add the no-LLM groups (policy-random runs; frozen DINOv3, DINO4Cells, DCM, OpenPhenom, Phenom, CellProfiler)

README.md

@@ -52,9 +52,10 @@ with in-loop triage VLM). Per image: `shape/tool_cache/` with `cell_crops_triage
 
 ### `task3_SSL/` — self-supervised representation learning
 
-SHAPE-ES vs ReAct (at SHAPE-ES's control frequency), each with gpt-5.6-luna and claude-sonnet-5-5, against a
-fixed-recipe search, the default DINOv3 fine-tune and frozen DINOv3, on a 25 % subset of each plate's training wells
-(seed 0). Scores on held-out wells: RxRx1 well mAP (HEPG2, RPE), RxRx3-core EFAAR recall (HUVEC).
+SHAPE-ES vs ReAct (at SHAPE-ES's control frequency), each with gpt-5.6-luna and claude-sonnet-5-5, against no-LLM
+baselines: fixed-recipe and random searches over the same levers, the default DINOv3 fine-tune, and frozen pretrained
+models (DINOv3, DINO4Cells, DCM, OpenPhenom, Phenom, CellProfiler). Training used a 25 % subset of each plate's
+training wells (seed 0). Scores on held-out wells: RxRx1 well mAP (HEPG2, RPE), RxRx3-core EFAAR recall (HUVEC).
 
 | archive | arm | HEPG2 | RPE | HUVEC |
 |---|---|---|---|---|
@@ -63,12 +64,18 @@ fixed-recipe search, the default DINOv3 fine-tune and frozen DINOv3, on a 25 % s
 | `react_<task>_s0_luna` | ReAct · gpt-5.6-luna | 0.0116 | 0.0040 | 0.220 |
 | `react_<task>_s0_sonnet` | ReAct · claude-sonnet-5-5 | 0.0021 | 0.0151 | 0.260 |
 | `policy_fixed_<task>_s0` | fixed recipe, no LLM | 0.0137 | 0.0331 | 0.300 |
+| `policy_random_<task>_s0` | random search, no LLM | 0.0147 | 0.0380 | 0.287 |
 | `default_<task>_s0` | default fine-tune | 0.0086 | 0.0198 | 0.262 |
-| (`summary`) | frozen DINOv3 | 0.0145 | 0.0237 | 0.293 |
+| `frozen_models` | frozen DINOv3 | 0.0145 | 0.0237 | 0.293 |
+| `frozen_models` | frozen DINO4Cells-S / -B | 0.0150 / 0.0126 | 0.0295 / 0.0240 | 0.265 / 0.280 |
+| `frozen_models` | frozen DCM DINOv2-B | 0.0072 | 0.0168 | 0.268 |
+| `frozen_models` | frozen OpenPhenom | 0.0058 | 0.0090 | 0.267 |
+| `frozen_models` | Phenom-1 / Phenom-2 / CellProfiler (released tables) | — | — | 0.318 / 0.358 / 0.286 |
 
 Each run archive holds the agent trace (`agent_log.jsonl`), every LLM request and reply (`reasoner.jsonl`), every
 tool call with its training record (`tool_calls.jsonl`), run settings, the delivered model's record, per-call loss
-curves, the console log and the score; no checkpoints. Details: `logs/task3_SSL/README.md`. Code to rerun:
+curves, the console log and the score; no checkpoints. Frozen models train nothing, so `frozen_models` holds their
+scores, scorer outputs and embedding code instead. Details: `logs/task3_SSL/README.md`. Code to rerun:
 [SHAPE-Revision `repro-sweep`](https://github.com/xuekunwu/SHAPE-Revision/tree/repro-sweep/reproduce/sweep_2026_10).
 
 ## Unpack

logs/task3_SSL/README.md

@@ -16,8 +16,10 @@ Arms (every one has the same tool, lever menu, 8-round budget, 64-epoch cap and
 - `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 DINOv3 (no training, so no trace; its scores are in `summary.tar.zst`).
+- 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.
 
@@ -30,8 +32,22 @@ LLM arms ran with gpt-5.6-luna (`_luna`) and claude-sonnet-5-5 (`_sonnet`), reas
 | 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
 
@@ -47,6 +63,8 @@ One archive per run, `<arm>_<task>_s0[_<llm>].tar.zst`, unpacking to `<name>/`:
 - `run/react/` (ReAct only) — the ReAct session trace;
 - `lane.log` — the run's console log; `score.json` — its held-out score.
 
+`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

logs/task3_SSL/frozen_models.tar.zst

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logs/task3_SSL/policy_random_HEPG2_s0.tar.zst

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logs/task3_SSL/policy_random_HUVEC_s0.tar.zst

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logs/task3_SSL/policy_random_RPE_s0.tar.zst

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logs/task3_SSL/summary.tar.zst

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