Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261001T145641Z-lora-rank-sweep-calibration-budget/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores/ye2026_sepsis/cal_budget_20261001/fold0/README.md

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+# score_ft.py output: ye2026_sepsis, 17 scored donors
+
+Arms: zs__cal_n5, zs__cal_n10, zs__cal_n20, zs__cal_n40.  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 17 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) (2550 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 0.9969, coverage 1.0000.
+   **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
+   0.9961, coverage 1.0000.
+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 = 12) vs control groups ['adult_HC', 'adult_ICU_ctrl', 'ped_HC', 'ped_ICU_ctrl'] (n = 5); 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 12 + 5
+   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/20261001T145641Z-lora-rank-sweep-calibration-budget/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores/ye2026_sepsis/cal_budget_20261001/fold0/contrast.csv

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+arm,celltype,statistic,n_genes,r_generated,r_broadcast,partial_r_generated_given_broadcast,r_generated_vs_broadcast,n_case_donors_obs,n_control_donors_obs,n_case_donors_gen,n_control_donors_gen,n_cells_obs,n_cells_gen,deg_scored,top50_overlap,top50_jaccard,obs_top_list_size,gen_top_list_size,n_sig_obs,n_sig_gen,top50_overlap_broadcast,top50_jaccard_broadcast,broadcast_top_list_size,n_sig_broadcast
+zs__cal_n5,T cell,mean_cp10k,3276,0.2408323827697982,0.3537756378604929,0.16660448944455955,0.25481115508699376,12,5,12,5,61162,10925,,,,,,,,,,,
+zs__cal_n5,T cell,pseudobulk_log1p_cpm,3276,0.23263825080035994,0.3408167254639536,0.12278497831705357,0.3676082134027666,12,5,12,5,61162,10925,,,,,,,,,,,
+zs__cal_n5,B cell,mean_cp10k,3261,0.24381552834043468,0.45396775987634586,0.15098413534655308,0.2501571112085104,12,5,12,5,21022,3956,,,,,,,,,,,
+zs__cal_n5,B cell,pseudobulk_log1p_cpm,3261,0.22613065245102998,0.4431157699387226,0.14800007972429452,0.21811041347270457,12,5,12,5,21022,3956,,,,,,,,,,,
+zs__cal_n5,Monocyte,mean_cp10k,3260,0.38418235350153207,0.7038218362524818,0.24204055783182954,0.31390505355552234,12,5,12,5,31471,8035,,,,,,,,,,,
+zs__cal_n5,Monocyte,pseudobulk_log1p_cpm,3260,0.30905925936328743,0.7596107053187887,0.065508173506968,0.35441812778005766,12,5,12,5,31471,8035,,,,,,,,,,,
+zs__cal_n5,NK cell,mean_cp10k,3269,0.1347487731104594,0.3098653007706904,0.09213539104305425,0.15560055373457976,12,5,12,5,10457,1463,,,,,,,,,,,
+zs__cal_n5,NK cell,pseudobulk_log1p_cpm,3269,0.0009577221896339804,0.24161172743019657,-0.036959735673589594,0.15070798554490883,12,5,12,5,10457,1463,,,,,,,,,,,
+zs__cal_n5,T cell,welch_top50_deg,5975,,,,,12,5,12,5,61162,10925,True,0,0.0,50,0,113,0,0,0.0,0,0
+zs__cal_n5,B cell,welch_top50_deg,5975,,,,,12,5,12,5,21022,3956,True,0,0.0,50,16,164,16,0,0.0,0,0
+zs__cal_n5,Monocyte,welch_top50_deg,5975,,,,,12,5,12,5,31471,8035,True,0,0.0,50,0,932,0,0,0.0,0,0
+zs__cal_n5,NK cell,welch_top50_deg,5975,,,,,12,5,12,5,10457,1463,True,0,0.0,50,0,122,0,0,0.0,0,0
+zs__cal_n5,DC,welch_top50_deg,5975,,,,,12,5,11,5,1035,333,True,0,0.0,50,0,152,0,0,0.0,0,0
+zs__cal_n10,T cell,mean_cp10k,3276,0.22421041279347018,0.3558093221120106,0.14777416724174874,0.25481522051313776,12,5,12,5,61162,11148,,,,,,,,,,,
+zs__cal_n10,T cell,pseudobulk_log1p_cpm,3276,0.1755138571224213,0.34068163578112537,0.06523862013681866,0.3462845275517124,12,5,12,5,61162,11148,,,,,,,,,,,
+zs__cal_n10,B cell,mean_cp10k,3261,0.22639860289888733,0.45833254499027914,0.13894723444968426,0.23186301185256894,12,5,12,5,21022,3735,,,,,,,,,,,
+zs__cal_n10,B cell,pseudobulk_log1p_cpm,3261,0.25272023572005564,0.4431741618468719,0.17317494454907043,0.22929133662251006,12,5,12,5,21022,3735,,,,,,,,,,,
+zs__cal_n10,Monocyte,mean_cp10k,3260,0.38205492668162533,0.6985114696122215,0.23950900281918908,0.31399761764798106,12,5,12,5,31471,7988,,,,,,,,,,,
+zs__cal_n10,Monocyte,pseudobulk_log1p_cpm,3260,0.3003096683024056,0.7588439562197705,0.06191903497520876,0.34588475536637703,12,5,12,5,31471,7988,,,,,,,,,,,
+zs__cal_n10,NK cell,mean_cp10k,3269,0.1649086984231884,0.31624194675523215,0.12993260484049085,0.13526773625248617,12,5,12,5,10457,1508,,,,,,,,,,,
+zs__cal_n10,NK cell,pseudobulk_log1p_cpm,3269,0.04845696045780348,0.24167427622138,0.008841528803540416,0.1654947421735316,12,5,12,5,10457,1508,,,,,,,,,,,
+zs__cal_n10,T cell,welch_top50_deg,5975,,,,,12,5,12,5,61162,11148,True,0,0.0,50,0,113,0,0,0.0,0,0
+zs__cal_n10,B cell,welch_top50_deg,5975,,,,,12,5,12,5,21022,3735,True,0,0.0,50,2,164,2,0,0.0,0,0
+zs__cal_n10,Monocyte,welch_top50_deg,5975,,,,,12,5,12,5,31471,7988,True,0,0.0,50,0,932,0,0,0.0,0,0
+zs__cal_n10,NK cell,welch_top50_deg,5975,,,,,12,5,12,5,10457,1508,True,0,0.0,50,0,122,0,0,0.0,0,0
+zs__cal_n10,DC,welch_top50_deg,5975,,,,,12,5,11,5,1035,310,True,0,0.0,50,0,152,0,0,0.0,0,0
+zs__cal_n20,T cell,mean_cp10k,3276,0.22826141831175675,0.3542636600658898,0.15246788609436107,0.2551833222964095,12,5,12,5,61162,10922,,,,,,,,,,,
+zs__cal_n20,T cell,pseudobulk_log1p_cpm,3276,0.2060469277964946,0.3400840714577703,0.09437862311649656,0.36266337650214037,12,5,12,5,61162,10922,,,,,,,,,,,
+zs__cal_n20,B cell,mean_cp10k,3261,0.22917787353314747,0.45824516756055006,0.13877175620898005,0.23873806385166083,12,5,12,5,21022,3761,,,,,,,,,,,
+zs__cal_n20,B cell,pseudobulk_log1p_cpm,3261,0.24251704411373012,0.44258540537494245,0.16048570515418603,0.23163748216170243,12,5,12,5,21022,3761,,,,,,,,,,,
+zs__cal_n20,Monocyte,mean_cp10k,3260,0.40047488287230787,0.7039244059898121,0.24478952932172407,0.3363065379083324,12,5,12,5,31471,8198,,,,,,,,,,,
+zs__cal_n20,Monocyte,pseudobulk_log1p_cpm,3260,0.3322381860140783,0.7590595661630952,0.09217151475918908,0.36406979769234216,12,5,12,5,31471,8198,,,,,,,,,,,
+zs__cal_n20,NK cell,mean_cp10k,3269,0.12257526619181966,0.3155359005929266,0.07417050052501462,0.16860677065070434,12,5,12,5,10457,1456,,,,,,,,,,,
+zs__cal_n20,NK cell,pseudobulk_log1p_cpm,3269,-0.02023735386925024,0.24161138221038866,-0.061199020370128636,0.15890781821429242,12,5,12,5,10457,1456,,,,,,,,,,,
+zs__cal_n20,T cell,welch_top50_deg,5975,,,,,12,5,12,5,61162,10922,True,0,0.0,50,0,113,0,0,0.0,0,0
+zs__cal_n20,B cell,welch_top50_deg,5975,,,,,12,5,12,5,21022,3761,True,0,0.0,50,4,164,4,0,0.0,0,0
+zs__cal_n20,Monocyte,welch_top50_deg,5975,,,,,12,5,12,5,31471,8198,True,0,0.0,50,0,932,0,0,0.0,0,0
+zs__cal_n20,NK cell,welch_top50_deg,5975,,,,,12,5,12,5,10457,1456,True,0,0.0,50,4,122,4,0,0.0,0,0
+zs__cal_n20,DC,welch_top50_deg,5975,,,,,12,5,12,5,1035,318,True,0,0.0,50,0,152,0,0,0.0,0,0
+zs__cal_n40,T cell,mean_cp10k,3276,0.25513983112241917,0.35867594266355773,0.17596497815077247,0.27045147736855196,12,5,12,5,61162,11263,,,,,,,,,,,
+zs__cal_n40,T cell,pseudobulk_log1p_cpm,3276,0.20850858068018333,0.33702421535791854,0.10480473321737999,0.34373770467611914,12,5,12,5,61162,11263,,,,,,,,,,,
+zs__cal_n40,B cell,mean_cp10k,3261,0.24203637596436275,0.46053197012177555,0.14273621938120692,0.25989819706077527,12,5,12,5,21022,4304,,,,,,,,,,,
+zs__cal_n40,B cell,pseudobulk_log1p_cpm,3261,0.23417893255889421,0.44035394324514077,0.14526630411644956,0.24461591387831796,12,5,12,5,21022,4304,,,,,,,,,,,
+zs__cal_n40,Monocyte,mean_cp10k,3260,0.3869368012651301,0.6949536146238975,0.24399495464475632,0.3173761513717974,12,5,12,5,31471,7393,,,,,,,,,,,
+zs__cal_n40,Monocyte,pseudobulk_log1p_cpm,3260,0.3162586457288505,0.7574950662364173,0.07491917644409624,0.35719705007899266,12,5,12,5,31471,7393,,,,,,,,,,,
+zs__cal_n40,NK cell,mean_cp10k,3269,0.1641565134091886,0.3147911504368361,0.10742409537532634,0.20441069291571864,12,5,12,5,10457,1416,,,,,,,,,,,
+zs__cal_n40,NK cell,pseudobulk_log1p_cpm,3269,0.021715319325648297,0.23949663282300532,-0.016513714359195995,0.1567877814450066,12,5,12,5,10457,1416,,,,,,,,,,,
+zs__cal_n40,T cell,welch_top50_deg,5975,,,,,12,5,12,5,61162,11263,True,0,0.0,50,0,113,0,0,0.0,0,0
+zs__cal_n40,B cell,welch_top50_deg,5975,,,,,12,5,12,5,21022,4304,True,0,0.0,50,4,164,4,0,0.0,0,0
+zs__cal_n40,Monocyte,welch_top50_deg,5975,,,,,12,5,12,5,31471,7393,True,0,0.0,50,1,932,1,0,0.0,0,0
+zs__cal_n40,NK cell,welch_top50_deg,5975,,,,,12,5,12,5,10457,1416,True,0,0.0,50,1,122,1,0,0.0,0,0
+zs__cal_n40,DC,welch_top50_deg,5975,,,,,12,5,12,5,1035,339,True,0,0.0,50,1,152,1,0,0.0,0,0

paper-releases/pbisc-diffusion/updates/20261001T145641Z-lora-rank-sweep-calibration-budget/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores/ye2026_sepsis/cal_budget_20261001/fold0/per_donor.csv

@@ -0,0 +1,69 @@
+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
+zs__cal_n5,Abd-PS19,ped_sepsis,1500,7984,150,0.4846666666666667,0.4622995991983968,0.09666666666666666,0.11209919839679358,0.304,0.2937124248496994,0.07733333333333334,0.05586172344689379,0.009333333333333334,0.0156563126252505,0.028,0.06037074148296593,0.10825250501002004,0.17976211899936204,0.8615317899148485,6,False,1.0,0.47333333333333333,0.9866666666666667,0.6933333333333334,30.4,29.37124248496994,1760.5,2111.0
+zs__cal_n5,Abd-PS23,ped_sepsis,1500,4309,150,0.466,0.2529589231840334,0.20066666666666666,0.3272220932931075,0.20533333333333334,0.32142028312833604,0.01,0.013460199582269667,0.006,0.002088651659317707,0.112,0.08284984915293572,0.49220515200742637,0.5708838013443897,0.8550621046826705,10,False,0.9466666666666667,0.5266666666666666,0.9266666666666666,0.6666666666666666,20.533333333333335,32.1420283128336,1551.0,1832.0
+zs__cal_n5,Abd-S123,adult_sepsis,1500,6299,150,0.37933333333333336,0.16986823305286552,0.036,0.08779171297031275,0.528,0.5027782187648833,0.015333333333333332,0.10938244165740593,0.010666666666666666,0.0007937767899666614,0.030666666666666665,0.1293856167645658,0.4891195427845691,0.7650207172461033,0.86875526275895,1,True,0.9866666666666667,0.6733333333333333,0.9666666666666667,0.7933333333333333,52.800000000000004,50.277821876488325,1657.5,2261.0
+zs__cal_n5,Abd-S39,adult_sepsis,1500,4291,150,0.26,0.13819622465625728,0.05,0.06152412025168958,0.586,0.6933115823817292,0.012666666666666666,0.049638778839431366,0.014666666666666666,0.0013982754602656724,0.07666666666666666,0.05593101841062689,0.311615629612367,0.9633289157537908,0.8753540232144583,3,False,0.9733333333333334,0.4533333333333333,0.96,0.6866666666666666,58.599999999999994,69.33115823817292,2140.5,3523.0
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paper-releases/pbisc-diffusion/updates/20261001T145641Z-lora-rank-sweep-calibration-budget/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores/ye2026_sepsis/cal_budget_20261001/fold0/summary.json

@@ -0,0 +1,1360 @@
+{
+ "schema": "paired_ft_scores.v1",
+ "dataset": "ye2026_sepsis",
+ "written_utc": "2026-10-01T14:21:04.087326+00:00",
+ "command": [
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/tools/score_ft.py",
+  "--dataset",
+  "ye2026_sepsis",
+  "--out",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scores/ye2026_sepsis/cal_budget_20261001/fold0",
+  "--threads",
+  "8",
+  "--arm",
+  "zs__cal_n5=/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/generated/ye2026_sepsis/fold0/zs__cal_n5.npz",
+  "--arm",
+  "zs__cal_n10=/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/generated/ye2026_sepsis/fold0/zs__cal_n10.npz",
+  "--arm",
+  "zs__cal_n20=/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/generated/ye2026_sepsis/fold0/zs__cal_n20.npz",
+  "--arm",
+  "zs__cal_n40=/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/generated/ye2026_sepsis/fold0/zs__cal_n40.npz",
+  "--case-groups",
+  "adult_sepsis,ped_sepsis",
+  "--control-groups",
+  "adult_HC,adult_ICU_ctrl,ped_HC,ped_ICU_ctrl"
+ ],
+ "arms": [
+  "zs__cal_n5",
+  "zs__cal_n10",
+  "zs__cal_n20",
+  "zs__cal_n40"
+ ],
+ "donors": [
+  "Abd-PS19",
+  "Abd-PS23",
+  "Abd-S123",
+  "Abd-S39",
+  "Abd-S47",
+  "Abd-S66",
+  "HC01",
+  "HC07",
+  "IC23",
+  "PHC03",
+  "PIC04",
+  "Res-PS25",
+  "Res-S139",
+  "Res-S26",
+  "Res-S77",
+  "Skin-S140",
+  "Uri-S147"
+ ],
+ "n_donors": 17,
+ "reference": {
+  "cache": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis",
+  "reference_sha256": "bac12da8a241652cb75100a1b082b2be56806c9bf2fd20ce6f927f19683ea5b8",
+  "features_sha256": "0cfda4b0cf1caf5e5319d071697c228d894e992fd090e2b3ed450bd6c9887d46",
+  "n_r1_cells": 2550,
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+    "density": 2.1365882352941177
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+  "observed_l1_loo_null_mean": 0.5132314215340571
+ },
+ "contrast_definition": {
+  "enabled": true,
+  "rule": "explicit --case-groups / --control-groups",
+  "group_source": "features groups",
+  "case_groups": [
+   "adult_sepsis",
+   "ped_sepsis"
+  ],
+  "control_groups": [
+   "adult_HC",
+   "adult_ICU_ctrl",
+   "ped_HC",
+   "ped_ICU_ctrl"
+  ],
+  "n_case_donors": 12,
+  "n_control_donors": 5,
+  "n_donors_in_neither": 0,
+  "case": [
+   true,
+   true,
+   true,
+   true,
+   true,
+   true,
+   false,
+   false,
+   false,
+   false,
+   false,
+   true,
+   true,
+   true,
+   true,
+   true,
+   true
+  ],
+  "ctrl": [
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