Initial NeurIPS 2026 release: backbones, flow heads, SciPlex3 Path-B teachers/students, paper-table result JSONs

MANIFEST.json

@@ -0,0 +1,2141 @@
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+        "path": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s5/flow_best.pt",
+        "size_mb": 54.7,
+        "files_in_dir": [
+          "config.json",
+          "eval.json",
+          "flow_best.pt",
+          "reproduce.sh"
+        ]
+      },
+      "hparams_top": {
+        "_state_dict_present": true,
+        "theta_dim": 2000,
+        "d_embed": 2410,
+        "y_mean": "<tensor shape=[1, 2000] dtype=torch.float32>",
+        "y_std": "<tensor shape=[1, 2000] dtype=torch.float32>",
+        "train_names": "<list len=161 sample=['2-Methoxyestradiol', 'A-366', 'ABT-737', 'AG-490', 'AMG-900']>"
+      },
+      "hparams_nested": {
+        "teacher_ckpts": [
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9/flow_best.pt"
+        ],
+        "dataset_h5ad": "datasets/scFATE/processed/sciplex3/sciplex3.h5ad",
+        "multiview": "data/drug_embeddings/sciplex3_multiview_v2.pt",
+        "ood_json": "data/sciplex3_split_v2b.json",
+        "output": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s5",
+        "reflow_K": 16,
+        "epochs": 30000,
+        "lr": 0.0003,
+        "wd": 0.0001,
+        "batch": 64,
+        "sigma": 0.3,
+        "teacher_sigma": 0.3,
+        "teacher_steps": 40,
+        "sigma_inf": 0.1,
+        "n_steps": 20,
+        "K_eval": 128,
+        "seed": 5,
+        "log_every": 2000,
+        "topk_de": 50,
+        "device": "cuda",
+        "d_hidden": 512,
+        "n_blocks": 4,
+        "dropout": 0.1,
+        "M_teachers": 18,
+        "teacher_prior_types": [
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr"
+        ],
+        "prior": "none"
+      }
+    },
+    {
+      "paper_row": "SciPlex3 mixed-18 K=16 student s6 (paper headline 70.0)",
+      "dataset": "SciPlex3",
+      "run_dir": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s6",
+      "backbone": "hf-assets/checkpoints/sciplex3/scFATE_epoch199_best.pt",
+      "h5ad_rel": "datasets/scFATE/processed/sciplex3/sciplex3.h5ad",
+      "training_script": "scripts/reflow_sciplex3_delta_flow_ensemble.py",
+      "seed": 6,
+      "result_json": "experiments/results/sciplex3_iter197_reflow_ensemble_mixed18_K16_N7.json",
+      "teacher": null,
+      "teachers": [
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9"
+      ],
+      "launch_script": null,
+      "checkpoint": {
+        "path": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s6/flow_best.pt",
+        "size_mb": 54.7,
+        "files_in_dir": [
+          "config.json",
+          "eval.json",
+          "flow_best.pt",
+          "reproduce.sh"
+        ]
+      },
+      "hparams_top": {
+        "_state_dict_present": true,
+        "theta_dim": 2000,
+        "d_embed": 2410,
+        "y_mean": "<tensor shape=[1, 2000] dtype=torch.float32>",
+        "y_std": "<tensor shape=[1, 2000] dtype=torch.float32>",
+        "train_names": "<list len=161 sample=['2-Methoxyestradiol', 'A-366', 'ABT-737', 'AG-490', 'AMG-900']>"
+      },
+      "hparams_nested": {
+        "teacher_ckpts": [
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9/flow_best.pt"
+        ],
+        "dataset_h5ad": "datasets/scFATE/processed/sciplex3/sciplex3.h5ad",
+        "multiview": "data/drug_embeddings/sciplex3_multiview_v2.pt",
+        "ood_json": "data/sciplex3_split_v2b.json",
+        "output": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s6",
+        "reflow_K": 16,
+        "epochs": 30000,
+        "lr": 0.0003,
+        "wd": 0.0001,
+        "batch": 64,
+        "sigma": 0.3,
+        "teacher_sigma": 0.3,
+        "teacher_steps": 40,
+        "sigma_inf": 0.1,
+        "n_steps": 20,
+        "K_eval": 128,
+        "seed": 6,
+        "log_every": 2000,
+        "topk_de": 50,
+        "device": "cuda",
+        "d_hidden": 512,
+        "n_blocks": 4,
+        "dropout": 0.1,
+        "M_teachers": 18,
+        "teacher_prior_types": [
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr"
+        ],
+        "prior": "none"
+      }
+    },
+    {
+      "paper_row": "SciPlex3 mixed-18 K=16 student s7 (paper headline 70.0)",
+      "dataset": "SciPlex3",
+      "run_dir": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s7",
+      "backbone": "hf-assets/checkpoints/sciplex3/scFATE_epoch199_best.pt",
+      "h5ad_rel": "datasets/scFATE/processed/sciplex3/sciplex3.h5ad",
+      "training_script": "scripts/reflow_sciplex3_delta_flow_ensemble.py",
+      "seed": 7,
+      "result_json": "experiments/results/sciplex3_iter197_reflow_ensemble_mixed18_K16_N7.json",
+      "teacher": null,
+      "teachers": [
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8",
+        "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9"
+      ],
+      "launch_script": null,
+      "checkpoint": {
+        "path": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s7/flow_best.pt",
+        "size_mb": 54.7,
+        "files_in_dir": [
+          "config.json",
+          "eval.json",
+          "flow_best.pt",
+          "reproduce.sh"
+        ]
+      },
+      "hparams_top": {
+        "_state_dict_present": true,
+        "theta_dim": 2000,
+        "d_embed": 2410,
+        "y_mean": "<tensor shape=[1, 2000] dtype=torch.float32>",
+        "y_std": "<tensor shape=[1, 2000] dtype=torch.float32>",
+        "train_names": "<list len=161 sample=['2-Methoxyestradiol', 'A-366', 'ABT-737', 'AG-490', 'AMG-900']>"
+      },
+      "hparams_nested": {
+        "teacher_ckpts": [
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8/flow_best.pt",
+          "runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9/flow_best.pt"
+        ],
+        "dataset_h5ad": "datasets/scFATE/processed/sciplex3/sciplex3.h5ad",
+        "multiview": "data/drug_embeddings/sciplex3_multiview_v2.pt",
+        "ood_json": "data/sciplex3_split_v2b.json",
+        "output": "runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s7",
+        "reflow_K": 16,
+        "epochs": 30000,
+        "lr": 0.0003,
+        "wd": 0.0001,
+        "batch": 64,
+        "sigma": 0.3,
+        "teacher_sigma": 0.3,
+        "teacher_steps": 40,
+        "sigma_inf": 0.1,
+        "n_steps": 20,
+        "K_eval": 128,
+        "seed": 7,
+        "log_every": 2000,
+        "topk_de": 50,
+        "device": "cuda",
+        "d_hidden": 512,
+        "n_blocks": 4,
+        "dropout": 0.1,
+        "M_teachers": 18,
+        "teacher_prior_types": [
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "none",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr",
+          "krr"
+        ],
+        "prior": "none"
+      }
+    }
+  ]
+}

README.md

@@ -0,0 +1,58 @@
+# scFATE — NeurIPS 2026
+
+Lie-algebraic conditional flow matching for zero-shot perturbation prediction in single cells. This repo contains all
+checkpoints and configs behind Table 1 in the paper. Datasets are split out into a separate repo:
+[`Angione-Lab/scFATE-datasets`](https://huggingface.co/datasets/Angione-Lab/scFATE-datasets).
+
+## Layout
+
+```
+backbones/<dataset>/                       — scFATE rotation autoencoders (load first)
+flow_heads/<dataset>/seed{1,2,3}/          — pure-flow heads on the rotation latent
+flow_heads/k562/base/                      — K562 flow teacher (for reflow)
+flow_heads/k562/reflow_K2_s1/              — K562 reflow K=2 student (paper headline 81.2 DA)
+sciplex3_path_b/teachers/{priorkrr,priornone}/s{1..9}/
+sciplex3_path_b/students/mixed18_K16/s{1..7}/   — mixed-18 K=16 distilled student (paper headline 70.0 DA)
+results/table1_inputs/                     — saved eval JSONs for reviewer audit
+REPRODUCE.md                               — paper reproduction guide
+MANIFEST.json                              — machine-readable run inventory
+```
+
+## Quickstart
+
+```python
+from huggingface_hub import snapshot_download
+import torch
+
+# 1. Pull the K562 paper-headline checkpoint
+ckpt_dir = snapshot_download("Angione-Lab/scFATE", allow_patterns="flow_heads/k562/reflow_K2_s1/*")
+ckpt = torch.load(f"{ckpt_dir}/flow_heads/k562/reflow_K2_s1/flow_best.pt", map_location="cpu", weights_only=False)
+
+# 2. The ckpt has every hparam at top-level; the velocity-network state_dict is at ckpt["v_net_state_dict"]
+print({k: v for k, v in ckpt.items() if not k.endswith("_state_dict") and not k.startswith("_")})
+```
+
+For end-to-end reproduction (backbone → flow → reflow → eval), see [`REPRODUCE.md`](./REPRODUCE.md).
+
+## Caveat (important for paper integrity)
+
+Table 1 of the paper reports `cos=0.491 / PDE=0.483` for the SciPlex3 (Path B) row. **These two values are not in any
+saved eval log on the original training machine.** Only the mean DA = 0.700 reproduces from
+`results/table1_inputs/sciplex3_iter214_multi_metric_router_ensemble.json`
+(`metric_da.tanimoto_morgan2048 = 0.7000`). The router pipeline only stored DA, not cos/PDE. We are re-running the
+SciPlex3 Path-B eval to compute proper cos/PDE for camera-ready; until then, treat the SciPlex3 row's continuous metrics
+as not-yet-reproduced.
+
+Norman cos/PDE in Table 1 differ from the saved JSONs by ~0.002 (rounding). K562 reflow cos/PDE differ by ~0.007 (likely
+rounding/transcription).
+
+## Citation
+
+```
+@inproceedings{ahmad2026scfate,
+  title={scFATE: Zero-shot Perturbation Prediction via Lie-Algebraic Conditional Flow Matching},
+  author={Ahmad, Farhan and Angione, Claudio and others},
+  booktitle={NeurIPS},
+  year={2026}
+}
+```

REPRODUCE.md

@@ -0,0 +1,88 @@
+# scFATE NeurIPS 2026 — Reproduce the Paper
+
+This directory ships every checkpoint behind the paper's Table 1 + a `reproduce.sh`
+for each run. All 31 paper-headline runs are listed below.
+
+## 0. Prerequisites
+
+```bash
+git clone https://huggingface.co/Angione-Lab/scFATE
+cd scFATE/code  # source code is in scfate-code submodule
+uv venv && uv pip install -e .  # or pip install -r requirements.txt
+```
+
+Then download datasets:
+```bash
+huggingface-cli download Angione-Lab/scFATE-datasets --local-dir datasets/scFATE/processed --repo-type dataset
+```
+
+## 1. Dependency graph
+
+```
+backbone (rotation autoencoder)         — hf-assets/checkpoints/<dataset>/
+    └─→ flow head (s1, s2, s3)          — runs/<dataset>_flow_*/flow_best.pt
+            └─→ reflow K=2 (K562)       — runs/*_reflow_K2_*_s1/flow_best.pt
+            └─→ teachers ×18 (SciPlex3) — runs/*_priorkrr_V2B_s{1..9}, *_priornone_V2B_s{1..9}
+                    └─→ student ×7     — runs/*_reflow_ensemble_mixed18_K16_V2B_s{1..7}
+```
+
+## 2. Per-run reproduction
+
+Each `runs/<run_dir>/` contains:
+- `flow_best.pt` — checkpoint with embedded hparams (load via `torch.load`, look at top-level keys or `ckpt['hparams']`)
+- `config.json` — extracted hparams + result-JSON pointer + dataset path
+- `reproduce.sh` — exact training command, ready to run
+- `flow_metrics.jsonl` — training trajectory
+- `krr_prior.pkl` — KRR-init prior (if `prior=krr`)
+
+## 3. Paper-headline runs
+
+| Paper row | Dataset | Run dir | Result JSON | Reproduce |
+|---|---|---|---|---|
+| Norman seed 1 | CRISPRa Norman | `runs/b200_norman_flow_e115_krrinit_s02_mask_30k` | `experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_K128.json` | `bash runs/b200_norman_flow_e115_krrinit_s02_mask_30k/reproduce.sh` |
+| Norman seed 2 | CRISPRa Norman | `runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed2` | `experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed2.json` | `bash runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed2/reproduce.sh` |
+| Norman seed 3 | CRISPRa Norman | `runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed3` | `experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed3.json` | `bash runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed3/reproduce.sh` |
+| RPE1 seed 1 | Replogle RPE1 | `runs/b200_rpe1_flow_block_krrinit_mask_30k_s1` | `experiments/results/fair_comparison/rpe1_rotation_vs_direct__flow__b200_rpe1_flow_block_krrinit_mask_30k_s1_rpe1_block_K128.json` | `bash runs/b200_rpe1_flow_block_krrinit_mask_30k_s1/reproduce.sh` |
+| K562 base flow (teacher for reflow) | Replogle K562 | `runs/b200_k562_flow_bs2048_krrinit_mask_30k` | `experiments/results/fair_comparison/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_K128.json` | `bash runs/b200_k562_flow_bs2048_krrinit_mask_30k/reproduce.sh` |
+| K562 reflow K=2 (paper headline 81.2) | Replogle K562 | `runs/b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1` | `experiments/results/fair_comparison/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1_reflow_K2_bracket1p0_ens5seed_sigmainf0p15_antithetic_Kper128.json` | `bash runs/b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1/reproduce.sh` |
+| SciPlex3 priornone teacher s1 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s1/reproduce.sh` |
+| SciPlex3 priorkrr teacher s1 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s1/reproduce.sh` |
+| SciPlex3 priornone teacher s2 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s2/reproduce.sh` |
+| SciPlex3 priorkrr teacher s2 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s2/reproduce.sh` |
+| SciPlex3 priornone teacher s3 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s3/reproduce.sh` |
+| SciPlex3 priorkrr teacher s3 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s3/reproduce.sh` |
+| SciPlex3 priornone teacher s4 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s4/reproduce.sh` |
+| SciPlex3 priorkrr teacher s4 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s4/reproduce.sh` |
+| SciPlex3 priornone teacher s5 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s5/reproduce.sh` |
+| SciPlex3 priorkrr teacher s5 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s5/reproduce.sh` |
+| SciPlex3 priornone teacher s6 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s6/reproduce.sh` |
+| SciPlex3 priorkrr teacher s6 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s6/reproduce.sh` |
+| SciPlex3 priornone teacher s7 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s7/reproduce.sh` |
+| SciPlex3 priorkrr teacher s7 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s7/reproduce.sh` |
+| SciPlex3 priornone teacher s8 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s8/reproduce.sh` |
+| SciPlex3 priorkrr teacher s8 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s8/reproduce.sh` |
+| SciPlex3 priornone teacher s9 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priornone_V2B_s9/reproduce.sh` |
+| SciPlex3 priorkrr teacher s9 | SciPlex3 | `runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9` | — | `bash runs/b200_sciplex3_delta_flow_mv_v2_sig0p3_priorkrr_V2B_s9/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s1 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s1` | `experiments/results/sciplex3_iter196_reflow_ensemble_mixed18_K16_N5.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s1/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s2 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s2` | `experiments/results/sciplex3_iter196_reflow_ensemble_mixed18_K16_N5.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s2/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s3 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s3` | `experiments/results/sciplex3_iter196_reflow_ensemble_mixed18_K16_N5.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s3/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s4 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s4` | `experiments/results/sciplex3_iter196_reflow_ensemble_mixed18_K16_N5.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s4/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s5 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s5` | `experiments/results/sciplex3_iter196_reflow_ensemble_mixed18_K16_N5.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s5/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s6 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s6` | `experiments/results/sciplex3_iter197_reflow_ensemble_mixed18_K16_N7.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s6/reproduce.sh` |
+| SciPlex3 mixed-18 K=16 student s7 (paper headline 70.0) | SciPlex3 | `runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s7` | `experiments/results/sciplex3_iter197_reflow_ensemble_mixed18_K16_N7.json` | `bash runs/b200_sciplex3_delta_flow_reflow_ensemble_mixed18_K16_V2B_s7/reproduce.sh` |
+
+## 4. Eval pipeline
+
+```bash
+.venv/bin/python scripts/eval_fair_comparison.py \\
+    --dataset <dataset_name> --flow_ckpt <run_dir>/flow_best.pt \\
+    --multiview data/gene_embeddings/<dataset>_multiview.pt --K_eval 128
+```
+
+## 5. Known caveats
+
+- SciPlex3 paper-row cosine (0.491) and PDE (0.483) numbers in Table 1 are not in any saved
+  results JSON; only mean DA = 0.700 reproduces from `iter214_multi_metric_router_ensemble.json`
+  (`metric_da.tanimoto_morgan2048`). Re-eval needed before final submission.
+- Norman cos/PDE in Table 1 differ by ~0.002 from `*_K128.json` (rounded).
+- K562 reflow cos/PDE in Table 1 differ by ~0.007 from the saved ensemble JSON.

backbones/k562/config.json

@@ -0,0 +1,6 @@
+{
+  "checkpoint": "scFATE_epoch700_periodic.pt",
+  "type": "scFATE rotation autoencoder",
+  "dataset": "k562",
+  "source_path_in_b200_repo": "hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt"
+}

backbones/k562/scFATE_epoch700_periodic.pt

@@ -0,0 +1,3 @@
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+size 52611157

backbones/norman/config.json

@@ -0,0 +1,6 @@
+{
+  "checkpoint": "scFATE_epoch100_periodic.pt",
+  "type": "scFATE rotation autoencoder",
+  "dataset": "norman",
+  "source_path_in_b200_repo": "hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt"
+}

backbones/norman/scFATE_epoch100_periodic.pt

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+size 50270278

backbones/norman_e115/config.json

@@ -0,0 +1,6 @@
+{
+  "checkpoint": "scFATE_epoch115_best.pt",
+  "type": "scFATE rotation autoencoder",
+  "dataset": "norman_e115",
+  "source_path_in_b200_repo": "runs/cam_norman_e115/scFATE_epoch115_best.pt"
+}

backbones/norman_e115/scFATE_epoch115_best.pt

@@ -0,0 +1,3 @@
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+size 29252259

backbones/rpe1/config.json

@@ -0,0 +1,6 @@
+{
+  "checkpoint": "scFATE_epoch350_periodic.pt",
+  "type": "scFATE rotation autoencoder",
+  "dataset": "rpe1",
+  "source_path_in_b200_repo": "hf-assets/checkpoints/rpe1/scFATE_epoch350_periodic.pt"
+}

backbones/rpe1/scFATE_epoch350_periodic.pt

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+size 65188742

backbones/sciplex3/config.json

@@ -0,0 +1,6 @@
+{
+  "checkpoint": "scFATE_epoch199_best.pt",
+  "type": "scFATE rotation autoencoder",
+  "dataset": "sciplex3",
+  "source_path_in_b200_repo": "hf-assets/checkpoints/sciplex3/scFATE_epoch199_best.pt"
+}

backbones/sciplex3/scFATE_epoch199_best.pt

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+size 34859666

flow_heads/k562/base/config.json

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+{
+  "paper_row": "K562 base flow (teacher for reflow)",
+  "dataset": "Replogle K562",
+  "run_dir": "runs/b200_k562_flow_bs2048_krrinit_mask_30k",
+  "backbone": "hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt",
+  "h5ad_rel": "datasets/scFATE/processed/replogle_k562/replogle_k562.h5ad",
+  "training_script": "scripts/train_flow.py",
+  "seed": 1,
+  "result_json": "experiments/results/fair_comparison/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_K128.json",
+  "teacher": null,
+  "teachers": null,
+  "launch_script": "runs/launch_tx_bch_combo.sh",
+  "checkpoint": {
+    "path": "runs/b200_k562_flow_bs2048_krrinit_mask_30k/flow_best.pt",
+    "size_mb": 46.5,
+    "files_in_dir": [
+      "config.json",
+      "flow_best.pt",
+      "flow_metrics.jsonl",
+      "krr_prior.pkl",
+      "reproduce.sh"
+    ]
+  },
+  "hparams_top": {
+    "_v_net_state_dict_present": true,
+    "theta_dim": 192,
+    "d_embed": 1824,
+    "d_hidden": 512,
+    "n_blocks": 4,
+    "sigma": 0.05,
+    "n_steps": 20,
+    "epoch": 28000,
+    "loss": 3.408003710949113e-05,
+    "pert_names": "<list len=1093 sample=['AAMP', 'AARS', 'AATF', 'ABCB7', 'ABCE1']>",
+    "mv_gene_names": "<list len=1085 sample=['AAMP', 'AARS', 'AATF', 'ABCB7', 'ABCE1']>",
+    "prior": "krr",
+    "krr_gamma": 0.01,
+    "krr_alpha": 1.0
+  },
+  "hparams_nested": {}
+}

flow_heads/k562/base/flow_best.pt

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+size 48807691

flow_heads/k562/base/flow_metrics.jsonl

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flow_heads/k562/base/krr_prior.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:04466eddd84193b892d70eab064ad29222aee31ec8fa6aa33f770f26044ac147
+size 6581197

flow_heads/k562/base/reproduce.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+# Reproduce: K562 base flow (teacher for reflow)
+# Run dir:   runs/b200_k562_flow_bs2048_krrinit_mask_30k
+# Result:    experiments/results/fair_comparison/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_K128.json
+# Original launch: runs/launch_tx_bch_combo.sh
+# Backbone (rotation autoencoder, must be loaded first): hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt
+
+set -euo pipefail
+REPO=${REPO:-/workspace/research/scFATE}
+cd "$REPO"
+DATASET="datasets/scFATE/processed/replogle_k562/replogle_k562.h5ad"
+BACKBONE="hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt"
+RUN_DIR="runs/b200_k562_flow_bs2048_krrinit_mask_30k"
+
+.venv/bin/python -u scripts/train_flow.py \
+    --dataset_h5ad "$DATASET" \
+    --backbone_ckpt "$BACKBONE" \
+    --output "$RUN_DIR" \
+    --seed 1 \
+    --theta_dim 192 \
+    --d_embed 1824 \
+    --d_hidden 512 \
+    --n_blocks 4 \
+    --n_steps 20 \
+    --sigma 0.05 \
+    --krr_alpha 1.0 \
+    --krr_gamma 0.01 \
+    --prior 'krr'

flow_heads/k562/reflow_K2_s1/config.json

@@ -0,0 +1,58 @@
+{
+  "paper_row": "K562 reflow K=2 (paper headline 81.2)",
+  "dataset": "Replogle K562",
+  "run_dir": "runs/b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1",
+  "backbone": "hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt",
+  "h5ad_rel": "datasets/scFATE/processed/replogle_k562/replogle_k562.h5ad",
+  "training_script": "scripts/reflow_k562_delta_flow.py",
+  "seed": 1,
+  "result_json": "experiments/results/fair_comparison/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1_reflow_K2_bracket1p0_ens5seed_sigmainf0p15_antithetic_Kper128.json",
+  "teacher": "runs/b200_k562_flow_bs2048_krrinit_mask_30k",
+  "teachers": null,
+  "launch_script": "runs/launch_iter174_ens5_Kper256_and_train_s6_s10.sh",
+  "checkpoint": {
+    "path": "runs/b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1/flow_best.pt",
+    "size_mb": 46.5,
+    "files_in_dir": [
+      "config.json",
+      "flow_best.pt",
+      "flow_metrics.jsonl",
+      "krr_prior.pkl",
+      "reproduce.sh"
+    ]
+  },
+  "hparams_top": {
+    "_v_net_state_dict_present": true,
+    "theta_dim": 192,
+    "d_embed": 1824,
+    "d_hidden": 512,
+    "n_blocks": 4,
+    "sigma": 0.05,
+    "n_steps": 20,
+    "epoch": 21000,
+    "loss": 0.002288587740622461,
+    "pert_names": "<list len=1093 sample=['AAMP', 'AARS', 'AATF', 'ABCB7', 'ABCE1']>",
+    "mv_gene_names": "<list len=1085 sample=['AAMP', 'AARS', 'AATF', 'ABCB7', 'ABCE1']>",
+    "prior": "krr",
+    "krr_gamma": 0.01,
+    "krr_alpha": 1.0,
+    "head_kind": "flat",
+    "d_block_head": 16,
+    "velocity_arch": "mlp",
+    "teacher_arch": "mlp",
+    "tx_d_token": 128,
+    "tx_n_layers": 4,
+    "tx_n_heads": 4,
+    "tx_mlp_mult": 4.0,
+    "cfg_drop": 0.0,
+    "rectified_from": "runs/b200_k562_flow_bs2048_krrinit_mask_30k/flow_best.pt",
+    "rectified_K": 2,
+    "rectified_teacher_n_steps": 20,
+    "target_noise_sigma": 0.0,
+    "t_sampling": "uniform",
+    "bch_aug_rate": 0.0,
+    "bch_embed_mode": "mean",
+    "bracket_reg": 1.0
+  },
+  "hparams_nested": {}
+}

flow_heads/k562/reflow_K2_s1/flow_best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b1c30fef5a275d495aea10c63a8418d059076910fe15a26bbdcd678d8fe2395
+size 48808267

flow_heads/k562/reflow_K2_s1/flow_metrics.jsonl

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+{"epoch": 1000, "loss": 0.004366907058283687, "recon_cos": 0.3213195502758026, "recon_mse": 0.007488366682082415, "lr": 0.000299184875142442, "elapsed": 9.939256191253662}
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flow_heads/k562/reflow_K2_s1/krr_prior.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:04466eddd84193b892d70eab064ad29222aee31ec8fa6aa33f770f26044ac147
+size 6581197

flow_heads/k562/reflow_K2_s1/reproduce.sh

@@ -0,0 +1,45 @@
+#!/bin/bash
+# Reproduce: K562 reflow K=2 (paper headline 81.2)
+# Run dir:   runs/b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1
+# Result:    experiments/results/fair_comparison/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1_reflow_K2_bracket1p0_ens5seed_sigmainf0p15_antithetic_Kper128.json
+# Original launch: runs/launch_iter174_ens5_Kper256_and_train_s6_s10.sh
+# Backbone (rotation autoencoder, must be loaded first): hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt
+
+set -euo pipefail
+REPO=${REPO:-/workspace/research/scFATE}
+cd "$REPO"
+DATASET="datasets/scFATE/processed/replogle_k562/replogle_k562.h5ad"
+BACKBONE="hf-assets/checkpoints/crispri_k562/scFATE_epoch700_periodic.pt"
+RUN_DIR="runs/b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1"
+
+.venv/bin/python -u scripts/reflow_k562_delta_flow.py \
+    --dataset_h5ad "$DATASET" \
+    --backbone_ckpt "$BACKBONE" \
+    --output "$RUN_DIR" \
+    --seed 1 \
+    --theta_dim 192 \
+    --d_embed 1824 \
+    --d_hidden 512 \
+    --n_blocks 4 \
+    --n_steps 20 \
+    --sigma 0.05 \
+    --krr_alpha 1.0 \
+    --krr_gamma 0.01 \
+    --prior 'krr' \
+    --head_kind 'flat' \
+    --velocity_arch 'mlp' \
+    --t_sampling 'uniform' \
+    --target_noise_sigma 0.0 \
+    --rectified_K 2 \
+    --rectified_from 'runs/b200_k562_flow_bs2048_krrinit_mask_30k/flow_best.pt' \
+    --rectified_teacher_n_steps 20 \
+    --bracket_reg 1.0 \
+    --cfg_drop 0.0 \
+    --bch_aug_rate 0.0 \
+    --bch_embed_mode 'mean' \
+    --tx_d_token 128 \
+    --tx_n_layers 4 \
+    --tx_n_heads 4 \
+    --tx_mlp_mult 4.0 \
+    --d_block_head 16 \
+    --teacher_arch 'mlp'

flow_heads/norman/seed1/config.json

@@ -0,0 +1,41 @@
+{
+  "paper_row": "Norman seed 1",
+  "dataset": "CRISPRa Norman",
+  "run_dir": "runs/b200_norman_flow_e115_krrinit_s02_mask_30k",
+  "backbone": "hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt",
+  "h5ad_rel": "datasets/scFATE/processed/CRISPRa-norman/norman2019_gears_split.h5ad",
+  "training_script": "scripts/train_flow.py",
+  "seed": 1,
+  "result_json": "experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_K128.json",
+  "teacher": null,
+  "teachers": null,
+  "launch_script": null,
+  "checkpoint": {
+    "path": "runs/b200_norman_flow_e115_krrinit_s02_mask_30k/flow_best.pt",
+    "size_mb": 46.5,
+    "files_in_dir": [
+      "config.json",
+      "flow_best.pt",
+      "flow_metrics.jsonl",
+      "krr_prior.pkl",
+      "reproduce.sh"
+    ]
+  },
+  "hparams_top": {
+    "_v_net_state_dict_present": true,
+    "theta_dim": 192,
+    "d_embed": 1824,
+    "d_hidden": 512,
+    "n_blocks": 4,
+    "sigma": 0.02,
+    "n_steps": 20,
+    "epoch": 28500,
+    "loss": 0.000217468106711749,
+    "pert_names": "<list len=108 sample=['1', '2', 'AHR', 'ARID1A', 'ARRDC3']>",
+    "mv_gene_names": "<list len=104 sample=['AHR', 'ARID1A', 'ARRDC3', 'ATL1', 'BAK1']>",
+    "prior": "krr",
+    "krr_gamma": 0.01,
+    "krr_alpha": 1.0
+  },
+  "hparams_nested": {}
+}

flow_heads/norman/seed1/flow_best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8321a5e46a8f0e07082a110a6522846d4fd7416eec9975f7c73fa56db5002211
+size 48778123

flow_heads/norman/seed1/flow_metrics.jsonl

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flow_heads/norman/seed1/krr_prior.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed54b2612b50268760dc710e28dc0eca0f26b9162bfd5ab3c309af3e855f9c1a
+size 613987

flow_heads/norman/seed1/reproduce.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+# Reproduce: Norman seed 1
+# Run dir:   runs/b200_norman_flow_e115_krrinit_s02_mask_30k
+# Result:    experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_K128.json
+# Original launch: unknown
+# Backbone (rotation autoencoder, must be loaded first): hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt
+
+set -euo pipefail
+REPO=${REPO:-/workspace/research/scFATE}
+cd "$REPO"
+DATASET="datasets/scFATE/processed/CRISPRa-norman/norman2019_gears_split.h5ad"
+BACKBONE="hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt"
+RUN_DIR="runs/b200_norman_flow_e115_krrinit_s02_mask_30k"
+
+.venv/bin/python -u scripts/train_flow.py \
+    --dataset_h5ad "$DATASET" \
+    --backbone_ckpt "$BACKBONE" \
+    --output "$RUN_DIR" \
+    --seed 1 \
+    --theta_dim 192 \
+    --d_embed 1824 \
+    --d_hidden 512 \
+    --n_blocks 4 \
+    --n_steps 20 \
+    --sigma 0.02 \
+    --krr_alpha 1.0 \
+    --krr_gamma 0.01 \
+    --prior 'krr'

flow_heads/norman/seed2/config.json

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+{
+  "paper_row": "Norman seed 2",
+  "dataset": "CRISPRa Norman",
+  "run_dir": "runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed2",
+  "backbone": "hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt",
+  "h5ad_rel": "datasets/scFATE/processed/CRISPRa-norman/norman2019_gears_split.h5ad",
+  "training_script": "scripts/train_flow.py",
+  "seed": 2,
+  "result_json": "experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed2.json",
+  "teacher": null,
+  "teachers": null,
+  "launch_script": null,
+  "checkpoint": {
+    "path": "runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed2/flow_best.pt",
+    "size_mb": 46.5,
+    "files_in_dir": [
+      "config.json",
+      "flow_best.pt",
+      "flow_metrics.jsonl",
+      "krr_prior.pkl",
+      "reproduce.sh"
+    ]
+  },
+  "hparams_top": {
+    "_v_net_state_dict_present": true,
+    "theta_dim": 192,
+    "d_embed": 1824,
+    "d_hidden": 512,
+    "n_blocks": 4,
+    "sigma": 0.02,
+    "n_steps": 20,
+    "epoch": 29000,
+    "loss": 0.0001306741796724964,
+    "pert_names": "<list len=108 sample=['1', '2', 'AHR', 'ARID1A', 'ARRDC3']>",
+    "mv_gene_names": "<list len=104 sample=['AHR', 'ARID1A', 'ARRDC3', 'ATL1', 'BAK1']>",
+    "prior": "krr",
+    "krr_gamma": 0.01,
+    "krr_alpha": 1.0
+  },
+  "hparams_nested": {}
+}

flow_heads/norman/seed2/flow_best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4dab56cc4286ae62302f9f63d6d5a517b946885f49805d8942b5c2d8a994c16c
+size 48778123

flow_heads/norman/seed2/flow_metrics.jsonl

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flow_heads/norman/seed2/krr_prior.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed54b2612b50268760dc710e28dc0eca0f26b9162bfd5ab3c309af3e855f9c1a
+size 613987

flow_heads/norman/seed2/reproduce.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+# Reproduce: Norman seed 2
+# Run dir:   runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed2
+# Result:    experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed2.json
+# Original launch: unknown
+# Backbone (rotation autoencoder, must be loaded first): hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt
+
+set -euo pipefail
+REPO=${REPO:-/workspace/research/scFATE}
+cd "$REPO"
+DATASET="datasets/scFATE/processed/CRISPRa-norman/norman2019_gears_split.h5ad"
+BACKBONE="hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt"
+RUN_DIR="runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed2"
+
+.venv/bin/python -u scripts/train_flow.py \
+    --dataset_h5ad "$DATASET" \
+    --backbone_ckpt "$BACKBONE" \
+    --output "$RUN_DIR" \
+    --seed 2 \
+    --theta_dim 192 \
+    --d_embed 1824 \
+    --d_hidden 512 \
+    --n_blocks 4 \
+    --n_steps 20 \
+    --sigma 0.02 \
+    --krr_alpha 1.0 \
+    --krr_gamma 0.01 \
+    --prior 'krr'

flow_heads/norman/seed3/config.json

@@ -0,0 +1,41 @@
+{
+  "paper_row": "Norman seed 3",
+  "dataset": "CRISPRa Norman",
+  "run_dir": "runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed3",
+  "backbone": "hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt",
+  "h5ad_rel": "datasets/scFATE/processed/CRISPRa-norman/norman2019_gears_split.h5ad",
+  "training_script": "scripts/train_flow.py",
+  "seed": 3,
+  "result_json": "experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed3.json",
+  "teacher": null,
+  "teachers": null,
+  "launch_script": null,
+  "checkpoint": {
+    "path": "runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed3/flow_best.pt",
+    "size_mb": 46.5,
+    "files_in_dir": [
+      "config.json",
+      "flow_best.pt",
+      "flow_metrics.jsonl",
+      "krr_prior.pkl",
+      "reproduce.sh"
+    ]
+  },
+  "hparams_top": {
+    "_v_net_state_dict_present": true,
+    "theta_dim": 192,
+    "d_embed": 1824,
+    "d_hidden": 512,
+    "n_blocks": 4,
+    "sigma": 0.02,
+    "n_steps": 20,
+    "epoch": 29500,
+    "loss": 0.0001756271449266933,
+    "pert_names": "<list len=108 sample=['1', '2', 'AHR', 'ARID1A', 'ARRDC3']>",
+    "mv_gene_names": "<list len=104 sample=['AHR', 'ARID1A', 'ARRDC3', 'ATL1', 'BAK1']>",
+    "prior": "krr",
+    "krr_gamma": 0.01,
+    "krr_alpha": 1.0
+  },
+  "hparams_nested": {}
+}

flow_heads/norman/seed3/flow_best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9348ed5dfcbf59ac2a99463d64f006ac9287f4845ea6a2cef6ddc7495c747192
+size 48778123

flow_heads/norman/seed3/flow_metrics.jsonl

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flow_heads/norman/seed3/krr_prior.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed54b2612b50268760dc710e28dc0eca0f26b9162bfd5ab3c309af3e855f9c1a
+size 613987

flow_heads/norman/seed3/reproduce.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+# Reproduce: Norman seed 3
+# Run dir:   runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed3
+# Result:    experiments/results/fair_comparison/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed3.json
+# Original launch: unknown
+# Backbone (rotation autoencoder, must be loaded first): hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt
+
+set -euo pipefail
+REPO=${REPO:-/workspace/research/scFATE}
+cd "$REPO"
+DATASET="datasets/scFATE/processed/CRISPRa-norman/norman2019_gears_split.h5ad"
+BACKBONE="hf-assets/checkpoints/crispra_norman_r16/scFATE_epoch100_periodic.pt"
+RUN_DIR="runs/b200_norman_flow_e115_krrinit_s02_mask_30k_seed3"
+
+.venv/bin/python -u scripts/train_flow.py \
+    --dataset_h5ad "$DATASET" \
+    --backbone_ckpt "$BACKBONE" \
+    --output "$RUN_DIR" \
+    --seed 3 \
+    --theta_dim 192 \
+    --d_embed 1824 \
+    --d_hidden 512 \
+    --n_blocks 4 \
+    --n_steps 20 \
+    --sigma 0.02 \
+    --krr_alpha 1.0 \
+    --krr_gamma 0.01 \
+    --prior 'krr'

flow_heads/rpe1/seed1/config.json

@@ -0,0 +1,41 @@
+{
+  "paper_row": "RPE1 seed 1",
+  "dataset": "Replogle RPE1",
+  "run_dir": "runs/b200_rpe1_flow_block_krrinit_mask_30k_s1",
+  "backbone": "hf-assets/checkpoints/rpe1/scFATE_epoch350_periodic.pt",
+  "h5ad_rel": "datasets/scFATE/processed/replogle_rpe1/replogle_rpe1.h5ad",
+  "training_script": "scripts/train_flow.py",
+  "seed": 1,
+  "result_json": "experiments/results/fair_comparison/rpe1_rotation_vs_direct__flow__b200_rpe1_flow_block_krrinit_mask_30k_s1_rpe1_block_K128.json",
+  "teacher": null,
+  "teachers": null,
+  "launch_script": null,
+  "checkpoint": {
+    "path": "runs/b200_rpe1_flow_block_krrinit_mask_30k_s1/flow_best.pt",
+    "size_mb": 46.6,
+    "files_in_dir": [
+      "config.json",
+      "flow_best.pt",
+      "flow_metrics.jsonl",
+      "krr_prior.pkl",
+      "reproduce.sh"
+    ]
+  },
+  "hparams_top": {
+    "_v_net_state_dict_present": true,
+    "theta_dim": 192,
+    "d_embed": 1824,
+    "d_hidden": 512,
+    "n_blocks": 4,
+    "sigma": 0.05,
+    "n_steps": 20,
+    "epoch": 28500,
+    "loss": 5.099160883522321e-05,
+    "pert_names": "<list len=1544 sample=['AARS', 'AASDHPPT', 'AATF', 'ABCB10', 'ABCB7']>",
+    "mv_gene_names": "<list len=1524 sample=['AARS', 'AASDHPPT', 'AATF', 'ABCB10', 'ABCB7']>",
+    "prior": "krr",
+    "krr_gamma": 0.01,
+    "krr_alpha": 1.0
+  },
+  "hparams_nested": {}
+}

flow_heads/rpe1/seed1/flow_best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ecb4218950a4140683747cd6b04c11fbab10ed5c33a2492772c748f63f0943a6
+size 48821131

flow_heads/rpe1/seed1/flow_metrics.jsonl

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flow_heads/rpe1/seed1/krr_prior.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:824e857197f1c89ed19cfb5df49444539e5667f327bd3c8e97468b4245d478f6
+size 9221660

flow_heads/rpe1/seed1/reproduce.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+# Reproduce: RPE1 seed 1
+# Run dir:   runs/b200_rpe1_flow_block_krrinit_mask_30k_s1
+# Result:    experiments/results/fair_comparison/rpe1_rotation_vs_direct__flow__b200_rpe1_flow_block_krrinit_mask_30k_s1_rpe1_block_K128.json
+# Original launch: unknown
+# Backbone (rotation autoencoder, must be loaded first): hf-assets/checkpoints/rpe1/scFATE_epoch350_periodic.pt
+
+set -euo pipefail
+REPO=${REPO:-/workspace/research/scFATE}
+cd "$REPO"
+DATASET="datasets/scFATE/processed/replogle_rpe1/replogle_rpe1.h5ad"
+BACKBONE="hf-assets/checkpoints/rpe1/scFATE_epoch350_periodic.pt"
+RUN_DIR="runs/b200_rpe1_flow_block_krrinit_mask_30k_s1"
+
+.venv/bin/python -u scripts/train_flow.py \
+    --dataset_h5ad "$DATASET" \
+    --backbone_ckpt "$BACKBONE" \
+    --output "$RUN_DIR" \
+    --seed 1 \
+    --theta_dim 192 \
+    --d_embed 1824 \
+    --d_hidden 512 \
+    --n_blocks 4 \
+    --n_steps 20 \
+    --sigma 0.05 \
+    --krr_alpha 1.0 \
+    --krr_gamma 0.01 \
+    --prior 'krr'

results/table1_inputs/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_K128.json

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+{
+  "dataset": "crispra_norman_gears",
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+  "embedding": "data/gene_embeddings/genept_bge_large.pt",
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+  "bracket_scale": 2.4151077270507812,
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results/table1_inputs/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed2.json

@@ -0,0 +1,891 @@
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results/table1_inputs/norman_rotation_vs_direct__flow__b200_norman_flow_e115_krrinit_s02_mask_30k_seed3.json

@@ -0,0 +1,891 @@
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+}

results/table1_inputs/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_K128.json

@@ -0,0 +1,3330 @@
+{
+  "dataset": "replogle_k562",
+  "checkpoint": "runs/b200_replogle_k562_bs2048_s1/checkpoints/scFATE_epoch199_best.pt",
+  "embedding": "data/gene_embeddings/genept_bge_large.pt",
+  "n_eval": 271,
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+}

results/table1_inputs/replogle_rotation_vs_direct__flow__b200_k562_flow_bs2048_krrinit_mask_30k_reflow_K2_nomask_bracket1ep0_s1_reflow_K2_bracket1p0_ens5seed_sigmainf0p15_antithetic_Kper128.json

@@ -0,0 +1,3330 @@
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+}

results/table1_inputs/sciplex3_iter196_reflow_ensemble_mixed18_K16_N5.json

@@ -0,0 +1,995 @@
+{
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+  "date": "2026-04-24",
+  "dataset": "sciplex3",
+  "recipe": "reflow_ensemble_distillation_mixed18_K16",
+  "description": "mixed-18 K=16 distilled student N=5 extension (s4, s5) of iter195 N=3. Tests whether mixed-18 std stays <2pp at N=5 (reproducibility-winner hypothesis).",
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+        {
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+        {
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+        {
+          "drug": "Nintedanib",
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+          "mse_top20": 0.008941997773945332
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+        {
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+        {
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+        },
+        {
+          "drug": "Roxadustat",
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+        },
+        {
+          "drug": "SB431542",
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+          "mse_top20": 0.002609844319522381
+        },
+        {
+          "drug": "TMP195",
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+          "cos_topk": -0.4036948084831238,
+          "cos_full": -0.1491047739982605,
+          "mse_top20": 0.003192286705598235
+        },
+        {
+          "drug": "Toremifene",
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+          "cos_topk": 0.5694059133529663,
+          "cos_full": 0.31619495153427124,
+          "mse_top20": 0.003053051885217428
+        }
+      ]
+    }
+  },
+  "mixed18_N5_stats": {
+    "N": 5,
+    "mean": 0.6643199856281281,
+    "std_sample": 0.013441429480163173,
+    "min": 0.6439999866485596,
+    "max": 0.6799999874830246,
+    "range": 0.036000000834464974
+  },
+  "mixed18_N3_stats_iter195": {
+    "N": 3,
+    "mean": 0.6653333212931951,
+    "std_sample": 0.018903263375277268,
+    "min": 0.6439999866485596,
+    "max": 0.6799999874830246,
+    "range": 0.036000000834464974
+  },
+  "priornone9_N7_stats_iter193": {
+    "N": 7,
+    "mean": 0.6683428571428571,
+    "std_sample": 0.02760814234622683,
+    "min": 0.6136,
+    "max": 0.6944,
+    "range": 0.08079999999999998
+  },
+  "mixed18_N5_vs_priornone9_N7": {
+    "gap_pp": -0.40228715147290206,
+    "pooled_se_pp": 1.204248645936427,
+    "Z": -0.3340565528808068,
+    "within_noise": true
+  },
+  "std_shrinkage_N3_to_N5": {
+    "std_pp_N3": 1.8903263375277268,
+    "std_pp_N5": 1.3441429480163172,
+    "delta_pp": -0.5461833895114095,
+    "mixed18_lower_std_than_priornone9": true
+  },
+  "paper_table1_recommendation": {
+    "single_ckpt_efficiency_row": "mixed-18 K=16 N=5: DA=0.6643 +/- 1.34pp (sample std), gap vs priornone-9 N=7 = -0.40pp (Z=-0.33, within noise). Recommended over priornone-9 due to ~2x lower per-seed std.",
+    "primary_headline_row": "18-ckpt mixed V2B mean-PRED ensemble 69.44% DA (iter187, unchanged)",
+    "cheapest_reproducible_ensemble_row": "priornone-9 teacher ensemble 69.12% DA (iter184, unchanged)",
+    "split_sensitivity_row": "V1-split flow 67.36% vs DD-KRR 66.64% (iter188, unchanged)"
+  }
+}