Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores_masked/ye2026_sepsis/locoL_scratchsat_s150000_K1000/per_donor.csv

@@ -0,0 +1,83 @@
+arm,donor,group,n_generated_cells,n_observed_cells,n_reference_cells,gen_T cell,obs_T cell,gen_B cell,obs_B cell,gen_Monocyte,obs_Monocyte,gen_NK cell,obs_NK cell,gen_DC,obs_DC,gen_Other,obs_Other,comp_l1,comp_l1_obs_loo_null,pb_r,pb_own_rank,pb_top1,precision,coverage,precision_depth_matched,coverage_depth_matched,mono_pct_gen,mono_pct_obs,median_umi_gen,median_umi_obs
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paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores_masked/ye2026_sepsis/locoL_scratchsat_s150000_K1000/summary.json

@@ -0,0 +1,767 @@
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+   "coverage_dm": 0.5857723577235773,
+   "pb_r_median": 0.8971824796651219,
+   "pb_top1": 0.0975609756097561,
+   "mono_pct_gen": 20.091056910569108,
+   "mono_pct_obs": 20.817070783198325,
+   "median_umi_gen": 1047.0,
+   "median_umi_obs": 1967.0,
+   "contrast_mean_cp10k_r_gen": 0.24743003020643398,
+   "contrast_pseudobulk_log1p_cpm_r_gen": 0.12115221174290747,
+   "contrast_mean_cp10k_r_broadcast": 0.31594581626202867,
+   "contrast_pseudobulk_log1p_cpm_r_broadcast": 0.29096860411544245,
+   "deg_top50_T": 0,
+   "deg_top50_B": 0,
+   "deg_top50_Mono": 1,
+   "deg_top50_NK": 0,
+   "deg_top50_DC": 0,
+   "deg_top50_sum": 1,
+   "deg_top50_max": 250,
+   "deg_top50_sum_4type": 1,
+   "deg_top50_sum_broadcast": 21,
+   "seconds": 19.1
+  }
+ },
+ "per_arm": {
+  "locoL_scratchsat_s150000_K1000": {
+   "arm": "locoL_scratchsat_s150000_K1000",
+   "npz": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/generated_masked/ye2026_sepsis/hoL_ye2026_sepsis/locoL_scratchsat_s150000_K1000.npz",
+   "npz_sha256": "92c1eded1aadd1d8cce9a5233740be54080eb17fc6e1d759ae784d47338cef4d",
+   "receipt_verified": true,
+   "generation": {
+    "checkpoint": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/runs/hoL_ye2026_sepsis/K1000/scratchsat/checkpoint_ft_s150000.pt",
+    "checkpoint_sha256": "ad5f80e37ed3cb1a7f51570dead24cf06938afc656d1ff78dc2982f94858594b",
+    "input_condition_path": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/data/ye2026_sepsis/test_raw_K1000.npz",
+    "input_condition_sha256": "ffcc1562915493d43b6970aec5791ec01193f7ed72a0f8ab8103bb45ce46c641",
+    "seed": 20260927,
+    "steps": 50,
+    "support_readout": "bernoulli",
+    "weights": "ema"
+   },
+   "condition_for_broadcast": {
+    "path": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_crosscohort_20261002/data/ye2026_sepsis/test_raw_K1000.npz",
+    "sha256": "ffcc1562915493d43b6970aec5791ec01193f7ed72a0f8ab8103bb45ce46c641"
+   },
+   "poisson": {
+    "seed": 20260916,
+    "rule": "whole NPZ, rows in NPZ order",
+    "nnz_whole_npz": 27686534,
+    "median_library_whole_npz_panel": 1047.0,
+    "n_rows_whole_npz": 123000
+   },
+   "annotation": {
+    "model_pt_sha256": "bf3655899e5abee435340fc008656c4a17342da0f30b70cfd43de8e9223e1930",
+    "zero_padded_model_genes": 0,
+    "label_counts": {
+     "T cell": 51724,
+     "B cell": 26390,
+     "Monocyte": 24712,
+     "NK cell": 16301,
+     "DC": 2175,
+     "Other": 1698
+    },
+    "mean_l2_max_prob": 0.9333749811453064,
+    "predict_seconds": 5.1
+   },
+   "n_donors": 82,
+   "n_generated_cells": 123000,
+   "composition": {
+    "l1_mean": 0.5095358335741695,
+    "l1_median": 0.4446750062784175,
+    "l1_obs_loo_null_mean": 0.515468004498372,
+    "l1_generated_loo_mean_vs_observed_mean": 0.5786718602597141,
+    "composition_top1": 0.04878048780487805,
+    "mean_fraction_generated": {
+     "T cell": 0.42052,
+     "B cell": 0.214553,
+     "Monocyte": 0.200911,
+     "NK cell": 0.132528,
+     "DC": 0.017683,
+     "Other": 0.013805
+    },
+    "mean_fraction_observed": {
+     "T cell": 0.484547,
+     "B cell": 0.172757,
+     "Monocyte": 0.208171,
+     "NK cell": 0.080723,
+     "DC": 0.005542,
+     "Other": 0.04826
+    }
+   },
+   "pseudobulk": {
+    "n_genes": 5975,
+    "r_median": 0.8971824796651219,
+    "r_mean": 0.8929077521677818,
+    "top1": 0.0975609756097561,
+    "n_top1": 8,
+    "own_rank_median": 15.5,
+    "chance_top1": 0.012195121951219513
+   },
+   "precision_coverage": {
+    "precision": 0.8409756097560975,
+    "coverage": 0.3302439024390244,
+    "density": 0.3861626016260163,
+    "n_query": 12300,
+    "n_reference": 12300
+   },
+   "precision_coverage_depth_matched": {
+    "precision": 0.8404878048780487,
+    "coverage": 0.5857723577235773,
+    "density": 0.4786178861788618,
+    "detected_median_before": {
+     "R1": 411.0,
+     "Q": 219.0
+    },
+    "detected_median_after": {
+     "R1": 218.0,
+     "Q": 218.0
+    }
+   },
+   "monocyte_pct": {
+    "generated_mean_over_donors": 20.091056910569108,
+    "observed_mean_over_donors": 20.817070783198325,
+    "generated_pooled_cells": 20.091056910569105
+   },
+   "median_umi_per_cell_scoring_genes": {
+    "generated_pooled": 1047.0,
+    "observed_pooled": 1967.0,
+    "generated_mean_of_donor_medians": 1075.73779296875,
+    "observed_mean_of_donor_medians": 2112.9146341463415
+   },
+   "contrast": {
+    "mean_cp10k": {
+     "per_type": {
+      "T cell": {
+       "r_generated": 0.1505684168756165,
+       "r_broadcast": 0.2548893770824626,
+       "partial_r_generated_given_broadcast": 0.1615315597953561,
+       "r_generated_vs_broadcast": -0.021931947542911636,
+       "n_genes": 3258
+      },
+      "B cell": {
+       "r_generated": 0.2771112182661951,
+       "r_broadcast": 0.27458639801653467,
+       "partial_r_generated_given_broadcast": 0.24480060876889842,
+       "r_generated_vs_broadcast": 0.16346965990138454,
+       "n_genes": 3310
+      },
+      "Monocyte": {
+       "r_generated": 0.3426644422101362,
+       "r_broadcast": 0.5481103923782986,
+       "partial_r_generated_given_broadcast": 0.21032361340251848,
+       "r_generated_vs_broadcast": 0.3212347918950556,
+       "n_genes": 3289
+      },
+      "NK cell": {
+       "r_generated": 0.219376043473788,
+       "r_broadcast": 0.1861970975708186,
+       "partial_r_generated_given_broadcast": 0.18500720732313872,
+       "r_generated_vs_broadcast": 0.22757468329843314,
+       "n_genes": 3240
+      }
+     },
+     "mean_r_generated": 0.24743003020643398,
+     "mean_r_broadcast": 0.31594581626202867,
+     "mean_partial_r": 0.20041574732247794
+    },
+    "pseudobulk_log1p_cpm": {
+     "per_type": {
+      "T cell": {
+       "r_generated": 0.07083356900037616,
+       "r_broadcast": 0.2164745523777111,
+       "partial_r_generated_given_broadcast": 0.055207055105513166,
+       "r_generated_vs_broadcast": 0.07901192960257866,
+       "n_genes": 3258
+      },
+      "B cell": {
+       "r_generated": 0.2051689930995894,
+       "r_broadcast": 0.2711145517540278,
+       "partial_r_generated_given_broadcast": 0.1708308440755714,
+       "r_generated_vs_broadcast": 0.15785941772320108,
+       "n_genes": 3310
+      },
+      "Monocyte": {
+       "r_generated": 0.13774337503478365,
+       "r_broadcast": 0.6203629305570988,
+       "partial_r_generated_given_broadcast": -0.023376528171524472,
+       "r_generated_vs_broadcast": 0.25064789717700275,
+       "n_genes": 3289
+      },
+      "NK cell": {
+       "r_generated": 0.0708629098368807,
+       "r_broadcast": 0.05592238177293225,
+       "partial_r_generated_given_broadcast": 0.06617516195965631,
+       "r_generated_vs_broadcast": 0.0905291751659057,
+       "n_genes": 3240
+      }
+     },
+     "mean_r_generated": 0.12115221174290747,
+     "mean_r_broadcast": 0.29096860411544245,
+     "mean_partial_r": 0.0672091332423041
+    }
+   },
+   "deg_top50": {
+    "types_scored": [
+     "T cell",
+     "B cell",
+     "Monocyte",
+     "NK cell",
+     "DC"
+    ],
+    "types_not_scored": {},
+    "per_type": {
+     "T cell": {
+      "deg_scored": true,
+      "top50_overlap": 0,
+      "top50_jaccard": 0.0,
+      "obs_top_list_size": 50,
+      "gen_top_list_size": 2,
+      "top50_overlap_broadcast": 3,
+      "top50_jaccard_broadcast": 0.030927835051546393,
+      "n_cells_obs": 298117,
+      "n_cells_gen": 51724
+     },
+     "B cell": {
+      "deg_scored": true,
+      "top50_overlap": 0,
+      "top50_jaccard": 0.0,
+      "obs_top_list_size": 50,
+      "gen_top_list_size": 1,
+      "top50_overlap_broadcast": 2,
+      "top50_jaccard_broadcast": 0.02040816326530612,
+      "n_cells_obs": 99729,
+      "n_cells_gen": 26390
+     },
+     "Monocyte": {
+      "deg_scored": true,
+      "top50_overlap": 1,
+      "top50_jaccard": 0.013888888888888888,
+      "obs_top_list_size": 50,
+      "gen_top_list_size": 23,
+      "top50_overlap_broadcast": 13,
+      "top50_jaccard_broadcast": 0.14942528735632185,
+      "n_cells_obs": 111269,
+      "n_cells_gen": 24712
+     },
+     "NK cell": {
+      "deg_scored": true,
+      "top50_overlap": 0,
+      "top50_jaccard": 0.0,
+      "obs_top_list_size": 50,
+      "gen_top_list_size": 3,
+      "top50_overlap_broadcast": 2,
+      "top50_jaccard_broadcast": 0.02040816326530612,
+      "n_cells_obs": 47832,
+      "n_cells_gen": 16301
+     },
+     "DC": {
+      "deg_scored": true,
+      "top50_overlap": 0,
+      "top50_jaccard": 0.0,
+      "obs_top_list_size": 50,
+      "gen_top_list_size": 2,
+      "top50_overlap_broadcast": 1,
+      "top50_jaccard_broadcast": 0.010101010101010102,
+      "n_cells_obs": 3300,
+      "n_cells_gen": 2175
+     }
+    },
+    "sum": 1,
+    "sum_4type": 1,
+    "max": 250,
+    "mean": 0.2,
+    "sum_broadcast": 21,
+    "sum_broadcast_4type": 20,
+    "broadcast_n_significant": 1378,
+    "seconds": 0.25
+   },
+   "seconds": 19.1
+  }
+ },
+ "code_sha256": {
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/tools/score_ft.py": "ec5f40b4cea6d5062d0138f3b934abb6465e34cbfeac869c8a0906924c033aec",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/tools/ft_common.py": "4a6366b0f22208cd58714fc0261b8840c643b9d4569704d560cfd93534cbc747",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/utility_studies_final6k_20260925/umap/cell_immicro_5arm/tools/stage_b_embed.py": "d056cfdf38fb0e5f478756f370174e993b75d0c973c48e02e21749175a4ca2da",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/bulk2sc-paper/scripts/evaluate_generated_vs_truth.py": "48b12d794782b840838853e93e0fc55fab00532c4b3698f4588e926b985d2881",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/utility_studies_final6k_20260925/immicro/tools/immicro_common.py": "c5c30e917148cc5e664e91ea30c11bbdff9b6d1f53a3e0a13e16b1917eff37e9",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/aifi_scanvi_rebuild_20260916/predict_scanvi.py": "482ee5dcf4d72b54bc36cbb6dcff62e5030bc7afc46cb5fb01eca73a82ee45a5",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/aifi_scanvi_rebuild_20260916/poisson_readout.py": "8bfa080942fbcdc89ae23b276524a1a83266fb8cbc56b9af279e50f82e6cde38"
+ },
+ "seconds": 28.8
+}

paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores_masked/ye2026_sepsis/locoL_scratchsat_s162000_K1000/README.md

@@ -0,0 +1,73 @@
+# score_ft.py output: ye2026_sepsis, 82 scored donors
+
+Arms: locoL_scratchsat_s162000_K1000.  Every arm is scored on the same donors against the same observed reference.
+
+## Inputs and fixed contracts
+- Observed reference: `/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis/reference.npz` (sha bac12da8a241), built from datadir:/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ye2026_sepsis;
+  observed cells sum exactly to the features pseudobulk of every donor. Observed labels: /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis/observed_labels/labels/labels.parquet.
+- Generated cells: `generated_counts` read out once with Poisson(seed 20260916) over the **whole NPZ in row order**
+  (`poisson_readout.poisson_integerise`), then the scored donors' rows. These integer counts are used for labels, embedding,
+  depth and the contrast. Pseudobulk uses the summed `generated_counts` (rates), as `score_generated.py`.
+- Labels: frozen f01common scANVI (`predict_scanvi.py`, CPU, zero query epochs), six-type gate ['T cell', 'B cell', 'Monocyte', 'NK cell', 'DC', 'Other']; query genes =
+  the 1,006-gene annotation list minus genes the dataset's sc assay did not measure in every sample (1006 genes).
+- Scoring genes: 6k panel genes measured by both assays in every sample of the dataset (5975 genes).
+
+## Definitions
+1. **Composition**: fraction of each donor's cells per six-type label (all generated cells; all observed QC cells).
+   `comp_l1` = sum over the six labels of |generated - observed| (immicro_common.l1). `comp_l1_obs_loo_null` = L1 of the
+   donor's observed composition to the mean of the *other scored donors'* observed compositions. `composition_top1` =
+   fraction of donors whose generated composition is closest (L1) to their own observed composition.
+2. **Pseudobulk**: `pb_r` = Pearson r of CPM-log1p(summed generated_counts) vs CPM-log1p(observed pseudobulk) on the scoring
+   genes (evaluate_realbulk.cpm_log1p / paired_r). `pb_top1` = the donor's generated pseudobulk is closest (Pearson) to its own
+   observed pseudobulk among the 82 scored donors (immicro_common.retrieval = evaluate_realbulk.top1 arithmetic).
+3. **Precision / coverage / density** (stage_b_embed.py functions): per-cell CP10K over the scoring genes + log1p; PCA-50
+   (randomized, random_state 20260925) and k = 10 real-real k-NN balls fitted on **R1 of the scored donors only**.
+   Reference rule (independent of fold and arm): per donor, cells in canonical order (library_id+barcode), one
+   permutation from `default_rng([20260925, uint64(sha256(donor)[:8])])`; R1 = first n, R2 = next n,
+   n = min(150, n_cells // 2) (12300 R1 cells here). Generated query: per donor n cells (the donor's R1 size),
+   without replacement, `default_rng([20260926, same key])`. Precision = fraction of generated cells inside any R1 ball
+   (Kynkaanniemi 2019); coverage = fraction of R1 cells whose ball holds a generated cell; density = Naeem 2020.
+   Per-donor precision = that donor's generated cells; per-donor coverage = that donor's R1 cells (the pooled values are
+   their n-weighted means; plain means when every donor has 150 reference cells). R2 (held-out real cells of the same donors) is the
+   perfect-generator control: precision 0.9805, coverage 0.9997.
+   **Depth matched**: stage_b_embed depth matching run pairwise (R1 vs this arm): per donor and within-donor rank of detected
+   genes, both cells are thinned by UMI sampling without replacement to the smaller detected-gene count; PCA kept from
+   un-thinned R1, radii recomputed on thinned R1; fresh rng(20260929) per arm. R2 control: precision
+   0.9796, coverage 0.9998.
+4. **Monocyte %** = 100 x Monocyte fraction (all cells) per donor; **median UMI per cell** = median over cells of the
+   Poisson-read (generated) / observed counts summed over the scoring genes (per donor, and pooled).
+5. **Group contrast** (T, B, Monocyte, NK): case groups ['adult_sepsis', 'ped_sepsis'] (n = 61) vs control groups ['adult_HC', 'adult_ICU_ctrl', 'ped_HC', 'ped_ICU_ctrl'] (n = 21); rule: explicit --case-groups / --control-groups; groups from features groups.
+   Genes per type = scoring genes detected (count > 0) in >= 1 % of the scored donors' observed
+   cells of that type. Primary statistic `mean_cp10k`: per-cell CP10K over the scoring genes; per donor the mean over its
+   cells of the type (donors with >= 1 such cell); group mean = mean over the group's donors (donor-balanced);
+   logFC = log2(case mean + 1) - log2(control mean + 1). Secondary `pseudobulk_log1p_cpm`: the SLE benchmark evaluator's
+   statistic (donor x type summed counts, log1p CPM over the scoring genes, mean case - mean control;
+   evaluate_generated_vs_truth.group_log_fold_change). Both are computed on the generated cells (their frozen labels) and on
+   the observed cells; `r_generated` = Pearson r of the two logFC vectors. Broadcast baseline `r_broadcast`: the same
+   observed vector against the logFC of the input bulk (condition NPZ `bulk_counts` of the arm, scoring genes, per-donor
+   CP10K resp. log1p CPM, group means). `partial_r_generated_given_broadcast`: r of the OLS residuals of observed and
+   generated logFC on the bulk logFC (residual_specificity.py).
+6. **Top-50 DEG overlap** (contrast.csv rows `statistic = welch_top50_deg`; summary `deg_top50`): the SLE benchmark's score (`total_top50_overlap` of
+   `bulk2sc-paper/scripts/evaluate_generated_vs_truth.py`, Welch backend: the "top-50 DEG 81 / 84" of the final model), run
+   with the evaluator's own functions on the same donor x type pseudobulks as the contrast. Per cell type, observed and
+   generated separately: donor x type summed counts on all 5975 scoring genes (donors of the two groups with
+   >= 1 cell of the type) -> `welch_bh_deg` (log1p CPM, two-sided Welch t-test case vs control, Benjamini-Hochberg over the
+   genes with a defined p-value; needs >= 2 donors per group) -> `top_deg_genes` (FDR < 0.05, descending |logFC|,
+   first 50; shorter when fewer genes pass). `top50_overlap` = |observed list & generated list|; `top50_jaccard`
+   the evaluator's Jaccard. Summary `sum` = total over the scored types (the quantity reported as 81), `max` = the sum of
+   the observed list lengths (the "of 262"), `sum_4type` = T + B + Monocyte + NK. A type is scored when its observed test
+   is defined; an arm whose generated test is undefined for a scored type gets overlap 0. Types: T cell, B cell, Monocyte, NK cell, DC
+   (aggregates: /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis/deg_reference.npz).
+   **Broadcast analogue** (`top50_overlap_broadcast`, as `sle_broadcast.py` `broadcast_input_bulk`; not part of the
+   published benchmark): the same test on the arm's condition bulk_counts (scoring genes, the 61 + 21
+   donors), one whole-PBMC top-50 list, compared with every type's observed list.
+
+## Files
+- `per_donor.csv`: one row per arm x donor (all per-donor quantities above).
+- `summary.json`: per arm the donor means / pooled values, provenance (NPZ sha, receipt check, generation metadata,
+  Poisson nnz of the whole NPZ, annotation contract), and the reference block (PCA, R2 control).
+- `contrast.csv`: per arm x cell type x statistic (`mean_cp10k`, `pseudobulk_log1p_cpm`: logFC r; `welch_top50_deg`:
+  top-50 DEG overlap, T / B / Monocyte / NK / DC; columns of the other kind are empty).
+- `arms/<arm>/labels/` (predict_scanvi.py labels + manifest), `arms/<arm>/generated_cells.parquet` (NPZ row, donor, label,
+  UMI on the scoring genes, P/C subsample flag), `arms/<arm>/deg_top50_lists.csv` (observed, generated and broadcast
+  top-50 gene lists, Ensembl ids, rank order).

paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores_masked/ye2026_sepsis/locoL_scratchsat_s162000_K1000/arms/locoL_scratchsat_s162000_K1000/deg_top50_lists.csv

@@ -0,0 +1,338 @@
+celltype,source,rank,gene_id
+T cell,observed,1,ENSG00000123358
+T cell,observed,2,ENSG00000090382
+T cell,observed,3,ENSG00000143333
+T cell,observed,4,ENSG00000109321
+T cell,observed,5,ENSG00000124762
+T cell,observed,6,ENSG00000184113
+T cell,observed,7,ENSG00000144655
+T cell,observed,8,ENSG00000118515
+T cell,observed,9,ENSG00000184557
+T cell,observed,10,ENSG00000162772
+T cell,observed,11,ENSG00000232810
+T cell,observed,12,ENSG00000134531
+T cell,observed,13,ENSG00000277632
+T cell,observed,14,ENSG00000144290
+T cell,observed,15,ENSG00000112149
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