Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261004T051658Z-behcet-c1q-lora3/diffusion/dataset/server_1/model8/plans/behcet_c1q_lora3_20261004/README.md

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+# Behçet C1Q-high monocytes with LoRA on 3 recovered pairs (2026-10-04)
+
+**Question (user).** Can PBISC's paired LoRA reproduce a disease-specific subtype, the C1Q-high monocytes of
+Behçet's disease (Zheng 2022 PNAS)? The zero-shot final model reversed the group difference: BD < HC
+(utility_studies_final6k_20260925/behcet_probe).
+
+**Pairs.** BDV4–PBMC_BD_2, BDV5–PBMC_BD_3 and BDV6–PBMC_BD_4 were recovered blind to ages in
+`plans/behcet_pair_recovery_20261004`, and all three have equal ages. There is no HC pair.
+
+## Design
+
+- **Training.** LoRA r16 on the 3 BD pairs, using the LoRA-5 protocol: lr 5e-4, 3,000 fixed steps, batch 256, seed
+  20260927, real-bulk condition, fixed depth K = 1,000.
+  - Trainer: `paired_finetune_intradataset_20260927/tools/ft_sdd.py`, unchanged.
+  - 16,635 cells; 106 s on GB10; checkpoint sha `de5d7974…` (`runs/lora3/RUN.json`).
+- **Generation.** All 19 bulks, 5,000 cells each, DDIM 50, EMA weights, Bernoulli support. Two sampling seeds:
+  20260913 (the published Behçet seed) and 20261004.
+
+| arm | model | bulk input |
+|---|---|---|
+| zs_raw | final model, zero-shot | real bulk |
+| zs_cal | final model, zero-shot | bulk × α, gene-wise calibration fitted on the same 3 pairs |
+| lora3_raw | LoRA-3 | real bulk |
+
+- **Test rows.** The 6 BD bulks without sc (BDU1–3, BDV1–3) and all 10 HC bulks. None of them was seen in training.
+- **Scoring.** The earlier Behçet wrapper, unchanged (`behcet/tools/behcet_rules_and_groups.py`): frozen f01common
+  scANVI labels and Poisson read-out seed 20260916.
+  - Gene space: the 5,671-gene shared space ∩ genes measured in all 8 sc libraries = 5,658 genes, used for every arm.
+  - Rule A: C1Q-high = any C1Q gene detected. In generated arms rule A equals rule D, because rule D's 95th-percentile
+    threshold is 0 there. Rule B: ≥ 2 C1Q genes.
+- **Ground truth.** GSE198616 sc PBMC, 4 BD vs 4 HC, mostly different donors from the bulk. Scored at native depth
+  and thinned to each arm's monocyte depth.
+
+## Results (`out/group_table.csv`, `out/in_sample.csv`, `out/capability.csv`)
+
+**1. Group direction on the 16 held-out bulks.** C1Q-high share of monocytes, rule A; per-sample means BD / HC and the
+gap:
+
+| arm | seed 20260913 | seed 20261004 |
+|---|---|---|
+| zs_raw | 2.16 / 3.10, **−0.94 pp** (p 0.02) | 2.23 / 2.86, **−0.63 pp** (p 0.07) |
+| zs_cal | 4.54 / 3.43, **+1.11 pp** (p 0.18) | – |
+| lora3_raw | 4.86 / 3.95, **+0.91 pp** (p 0.26) | 5.28 / 3.55, **+1.72 pp** (p 0.02) |
+| observed, thinned to lora3 depth (4 vs 4) | 7.96 / 6.70, +1.26 pp (p 0.49) | |
+
+- **LoRA-3 turns the zero-shot reversal into the observed direction** in both seeds. The gap size (+0.9 to +1.7 pp)
+  brackets the observed +1.3 pp. The BD/HC ratio is 1.2–1.5; observed sc gives 1.2 and the authors' flow cytometry
+  1.75.
+- **Calibration fitted on the same 3 pairs does the same** (+1.1 pp). On the group direction, LoRA is not ahead of
+  calibration.
+- The seed-to-seed spread of the LoRA gap (0.8 pp) is as large as the gap itself. With 6 vs 10 held-out bulks this
+  is a direction result, not a precise effect size.
+
+**2. Composition is where most of the gain comes from.**
+- Monocytes as a share of all cells on held-out bulks, BD / HC: zs_raw 30.2 / 20.1, zs_cal 13.5 / 11.0, lora3 16.0 /
+  11.9. Observed sc gives 16.7 / 13.0.
+- Training donors, generated vs their own observed cells: LoRA 13.7 / 19.2 / 20.2 % vs observed 14.9 / 20.9 / 20.5 %;
+  zero-shot 23 / 44 / 44 %.
+
+**3. The C1Q-high state itself is still mostly missing.** Pooled monocytes of the held-out bulks, observed thinned to
+the same depth:
+
+| | any C1Q gene (rule A) | ≥ 2 C1Q genes (rule B) |
+|---|---|---|
+| zs_raw | 2.6 % (0.57× of 4.6 %) | 0.16 % (0.10× of 1.6 %) |
+| lora3_raw | 4.3 % (0.63× of 6.9 %) | 0.25–0.35 % (0.10–0.15× of 2.4 %) |
+
+Even for the 3 training donors, LoRA gives ≥ 2-gene C1Q cells at 0.5–1.1 % against 1.5–3.7 % observed. LoRA improves
+single-gene C1Q detection and composition. It does not create the multi-gene, high-UMI C1Q-high cells. This is the
+same limit the zero-shot probe found (value magnitude of rare genes below 1 UMI).
+
+## Verdict
+
+- **Disease direction: yes.** With 3 BD pairs, LoRA reproduces the BD > HC direction of C1Q-positive monocytes on
+  held-out bulks and fixes the monocyte over-production. Calibration on the same 3 pairs does as well on this readout.
+- **The subtype itself: not yet.** The generated "C1Q-high" cells are mostly single-gene C1Q detections in CD16-type
+  monocytes, not the multi-gene C1Q-high state. A claim that PBISC generates C1Q-high monocytes would overstate this.
+- **Limits.** 3 training pairs, all BD and all vascular type; no HC pair; 6 vs 10 test bulks; 2 seeds. The truth set
+  is 4 vs 4 other donors. Rule A is a weak definition at ~500 UMI per cell.
+
+## Files
+
+- `tools/build_dataset.py` → `data/behcet/` (features, cells, conditions, BUILD.json).
+- `tools/run_gpu.sh` (train + 5 sampling arms, read-out, labels; NPZs moved to spark-0110 at the same path with a
+  sha check, `generated/<arm>.moved`).
+- `tools/score_arms.sh` → `out/rules_groups/`.
+- `tools/summarize.py` → `out/{group_table,in_sample,capability}.csv`, `out/SUMMARY.json`.
+- Queue: `queues/arms.txt`. Logs: `logs/`.
+- GPU: interleaved with the scSemiProfiler CV queue through the shared lock (ml-run flock), never concurrent.

paper-releases/pbisc-diffusion/updates/20261004T051658Z-behcet-c1q-lora3/diffusion/dataset/server_1/model8/plans/behcet_c1q_lora3_20261004/data/behcet/alpha.npy

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paper-releases/pbisc-diffusion/updates/20261004T051658Z-behcet-c1q-lora3/diffusion/dataset/server_1/model8/plans/behcet_c1q_lora3_20261004/data/behcet/features.npz

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paper-releases/pbisc-diffusion/updates/20261004T051658Z-behcet-c1q-lora3/diffusion/dataset/server_1/model8/plans/behcet_c1q_lora3_20261004/queues/arms.txt

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+# TAG|CKPT (base | lora)|CONDITION_NPZ|SEED   (5,000 cells per bulk from the NPZ; DDIM 50, EMA, Bernoulli support)
+zs_raw_s13|base|/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/behcet_c1q_lora3_20261004/data/behcet/conditions_raw_fixed.npz|20260913
+zs_cal_s13|base|/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/behcet_c1q_lora3_20261004/data/behcet/conditions_cal_fixed.npz|20260913
+lora3_raw_s13|lora|/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/behcet_c1q_lora3_20261004/data/behcet/conditions_raw_fixed.npz|20260913
+lora3_raw_s04|lora|/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/behcet_c1q_lora3_20261004/data/behcet/conditions_raw_fixed.npz|20261004
+zs_raw_s04|base|/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/behcet_c1q_lora3_20261004/data/behcet/conditions_raw_fixed.npz|20261004