Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261008T125804Z-deck-fig2-3-healthy-fig5-rare/diffusion/dataset/server_1/model8/presentations/2026-09-30--paper-summary--r00/data/fig23_healthy.csv

@@ -0,0 +1,185 @@
+slide,design,metric,series,value,extra,source
+2e,5 donors (mean of 5 draws),coverage,zs_raw,0.190013,,data/sec09_fewpair_cells.csv
+2e,5 donors (mean of 5 draws),coverage,zs_cal,0.535242,,data/sec09_fewpair_cells.csv
+2e,5 donors (mean of 5 draws),coverage,lora,0.79247,,data/sec09_fewpair_cells.csv
+2e,5-fold pooled,coverage,zs_raw,0.191838,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,coverage,zs_cal,0.527227,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,coverage,sconly_cal,0.623302,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,coverage,lora,0.784299,,data/sec07_ft_modes_accuracy.csv
+2e,5 donors (mean of 5 draws),precision,zs_raw,0.677216,,data/sec09_fewpair_cells.csv
+2e,5 donors (mean of 5 draws),precision,zs_cal,0.903673,,data/sec09_fewpair_cells.csv
+2e,5 donors (mean of 5 draws),precision,lora,0.952078,,data/sec09_fewpair_cells.csv
+2e,5-fold pooled,precision,zs_raw,0.680436,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,precision,zs_cal,0.905047,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,precision,sconly_cal,0.804735,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,precision,lora,0.924112,,data/sec07_ft_modes_accuracy.csv
+2e,5 donors (mean of 5 draws),comp_l1,zs_raw,0.44511,,data/sec09_fewpair_cells.csv
+2e,5 donors (mean of 5 draws),comp_l1,zs_cal,0.202832,,data/sec09_fewpair_cells.csv
+2e,5 donors (mean of 5 draws),comp_l1,lora,0.17556,,data/sec09_fewpair_cells.csv
+2e,5-fold pooled,comp_l1,zs_raw,0.454866,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,comp_l1,zs_cal,0.198503,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,comp_l1,sconly_cal,0.240253,,data/sec07_ft_modes_accuracy.csv
+2e,5-fold pooled,comp_l1,lora,0.161729,,data/sec07_ft_modes_accuracy.csv
+2f,5 donors (mean of 5 draws),c2st_knn_auc,zs_raw,0.996552,,data/sec09_extra_fewpair.csv
+2f,5 donors (mean of 5 draws),c2st_knn_auc,zs_cal,0.973164,,data/sec09_extra_fewpair.csv
+2f,5 donors (mean of 5 draws),c2st_knn_auc,lora,0.942663,,data/sec09_extra_fewpair.csv
+2f,5-fold pooled,c2st_knn_auc,zs_raw,0.99636,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,c2st_knn_auc,zs_cal,0.972808,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,c2st_knn_auc,sconly_cal,0.952425,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,c2st_knn_auc,lora,0.940942,,data/sec09_extra_fivefold.csv
+2f,5 donors (mean of 5 draws),mmd2_bw1,zs_raw,0.102587,,data/sec09_extra_fewpair.csv
+2f,5 donors (mean of 5 draws),mmd2_bw1,zs_cal,0.0430417,,data/sec09_extra_fewpair.csv
+2f,5 donors (mean of 5 draws),mmd2_bw1,lora,0.0230837,,data/sec09_extra_fewpair.csv
+2f,5-fold pooled,mmd2_bw1,zs_raw,0.101883,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,mmd2_bw1,zs_cal,0.0425284,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,mmd2_bw1,sconly_cal,0.0341944,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,mmd2_bw1,lora,0.0263951,,data/sec09_extra_fivefold.csv
+2f,5 donors (mean of 5 draws),en_all_sq,zs_raw,7.23567,,data/sec09_extra_fewpair.csv
+2f,5 donors (mean of 5 draws),en_all_sq,zs_cal,2.85538,,data/sec09_extra_fewpair.csv
+2f,5 donors (mean of 5 draws),en_all_sq,lora,1.54716,,data/sec09_extra_fewpair.csv
+2f,5-fold pooled,en_all_sq,zs_raw,4.83231,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,en_all_sq,zs_cal,2.26259,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,en_all_sq,sconly_cal,1.76688,,data/sec09_extra_fivefold.csv
+2f,5-fold pooled,en_all_sq,lora,1.56042,,data/sec09_extra_fivefold.csv
+2g,pooled,comp_l1,full,0.157221,,data/sec07_ft_modes_accuracy.csv
+2g,pooled,comp_l1,lora,0.161729,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,comp_l1,full,0.147001,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,comp_l1,lora,0.152859,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,comp_l1,condenc,0.204182,,data/sec07_ft_modes_accuracy.csv
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+2g,pooled,coverage,lora,0.784299,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,coverage,full,0.841212,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,coverage,lora,0.914848,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,coverage,condenc,0.728485,,data/sec07_ft_modes_accuracy.csv
+2g,pooled,precision,full,0.889533,,data/sec07_ft_modes_accuracy.csv
+2g,pooled,precision,lora,0.924112,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,precision,full,0.98697,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,precision,lora,0.991515,,data/sec07_ft_modes_accuracy.csv
+2g,fold0,precision,condenc,0.979394,,data/sec07_ft_modes_accuracy.csv
+2g,,trainable_M,full,54.1852,,data/sec07_ft_modes_compute.csv
+2g,,trainable_M,lora,1.29622,,data/sec07_ft_modes_compute.csv
+2g,,trainable_M,condenc,9.48326,,data/sec07_ft_modes_compute.csv
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+2h,,comp_l1,lora,0.171451,pairs 5,data/sec08_pairs_realism.csv
+2h,,comp_l1,lora,0.187881,pairs 10,data/sec08_pairs_realism.csv
+2h,,comp_l1,lora,0.172324,pairs 20,data/sec08_pairs_realism.csv
+2h,,comp_l1,lora,0.171385,pairs 40,data/sec08_pairs_realism.csv
+2h,,comp_l1,lora,0.161729,pairs all,data/sec08_pairs_realism.csv
+2h,,coverage,zero_shot,0.191838,pairs 0,data/sec08_pairs_realism.csv
+2h,,coverage,zs_cal_budget,0.52704,pairs 5,data/sec08_pairs_realism.csv
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+2h,,coverage,zs_cal_budget,0.522368,pairs 40,data/sec08_pairs_realism.csv
+2h,,coverage,zs_cal_budget,0.527227,pairs all,data/sec08_pairs_realism.csv
+2h,,coverage,lora,0.83919,pairs 5,data/sec08_pairs_realism.csv
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+2h,,coverage,lora,0.755202,pairs 20,data/sec08_pairs_realism.csv
+2h,,coverage,lora,0.778442,pairs 40,data/sec08_pairs_realism.csv
+2h,,coverage,lora,0.784299,pairs all,data/sec08_pairs_realism.csv
+2h,,nk_fraction_r,zero_shot,0.493942,pairs 0,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,zs_cal_budget,0.501938,pairs 5,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,zs_cal_budget,0.514964,pairs 10,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,zs_cal_budget,0.525103,pairs 20,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,zs_cal_budget,0.499965,pairs 40,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,zs_cal_budget,0.500396,pairs all,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,lora,0.199274,pairs 5,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,lora,0.397169,pairs 10,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,lora,0.564359,pairs 20,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,lora,0.699336,pairs 40,data/sec08_pairs_signal.csv
+2h,,nk_fraction_r,lora,0.701926,pairs all,data/sec08_pairs_signal.csv
+2h,,selected_step_median_k,lora,3.25,pairs 5,data/sec08_selected_steps_per_fold.csv
+2h,,selected_step_median_k,lora,5.75,pairs 10,data/sec08_selected_steps_per_fold.csv
+2h,,selected_step_median_k,lora,19.5,pairs 20,data/sec08_selected_steps_per_fold.csv
+2h,,selected_step_median_k,lora,20,pairs 40,data/sec08_selected_steps_per_fold.csv
+2h,,selected_step_median_k,lora,20,pairs all,data/sec08_selected_steps_per_fold.csv
+2i,,comp_l1,lora_r4,0.162213,pairs 5,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r4,0.170952,pairs 20,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r4,0.185778,pairs all,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r16,0.171451,pairs 5,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r16,0.172324,pairs 20,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r16,0.161729,pairs all,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r64,0.176511,pairs 5,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r64,0.171654,pairs 20,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_r64,0.160951,pairs all,data/sec07_rank_sweep.csv
+2i,,comp_l1,lora_multik__raw,0.167777,pairs all,data/sec07_k_aug.csv
+2i,,comp_l1,lora_recipe__raw,0.16091,pairs all,data/sec07_k_aug.csv
+2i,,coverage,lora_r4,0.789097,pairs 5,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r4,0.714953,pairs 20,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r4,0.712336,pairs all,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r16,0.83919,pairs 5,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r16,0.755202,pairs 20,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r16,0.784299,pairs all,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r64,0.84729,pairs 5,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r64,0.793707,pairs 20,data/sec07_rank_sweep.csv
+2i,,coverage,lora_r64,0.815888,pairs all,data/sec07_rank_sweep.csv
+2i,,coverage,lora_multik__raw,0.774829,pairs all,data/sec07_k_aug.csv
+2i,,coverage,lora_recipe__raw,0.765545,pairs all,data/sec07_k_aug.csv
+2i,,precision,lora_r4,0.936885,pairs 5,data/sec07_rank_sweep.csv
+2i,,precision,lora_r4,0.924735,pairs 20,data/sec07_rank_sweep.csv
+2i,,precision,lora_r4,0.933333,pairs all,data/sec07_rank_sweep.csv
+2i,,precision,lora_r16,0.946293,pairs 5,data/sec07_rank_sweep.csv
+2i,,precision,lora_r16,0.920436,pairs 20,data/sec07_rank_sweep.csv
+2i,,precision,lora_r16,0.924112,pairs all,data/sec07_rank_sweep.csv
+2i,,precision,lora_r64,0.945545,pairs 5,data/sec07_rank_sweep.csv
+2i,,precision,lora_r64,0.905296,pairs 20,data/sec07_rank_sweep.csv
+2i,,precision,lora_r64,0.904424,pairs all,data/sec07_rank_sweep.csv
+2i,,precision,lora_multik__raw,0.928411,pairs all,data/sec07_k_aug.csv
+2i,,precision,lora_recipe__raw,0.93296,pairs all,data/sec07_k_aug.csv
+3a,5 donors (mean of 5 draws),coverage,zs_raw,0.190013,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),coverage,scsemi,0.0358301,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),coverage,lora,0.79247,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),precision,zs_raw,0.677216,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),precision,scsemi,0.518,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),precision,lora,0.952078,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),comp_l1,zs_raw,0.44511,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),comp_l1,scsemi,0.232512,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),comp_l1,lora,0.17556,,data/sec09_fewpair_cells.csv
+3a,5 donors (mean of 5 draws),c2st_knn_auc,zs_raw,0.996552,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),c2st_knn_auc,scsemi,0.998799,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),c2st_knn_auc,lora,0.942663,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),mmd2_bw1,zs_raw,0.102587,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),mmd2_bw1,scsemi,0.186497,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),mmd2_bw1,lora,0.0230837,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),en_all_sq,zs_raw,7.23567,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),en_all_sq,scsemi,3.64912,,data/sec09_extra_fewpair.csv
+3a,5 donors (mean of 5 draws),en_all_sq,lora,1.54716,,data/sec09_extra_fewpair.csv
+3b,,comp_l1,scsemi,0.218449,pairs 5,data/sec08_pairs_realism.csv
+3b,,comp_l1,scsemi,0.226932,pairs 10,data/sec08_pairs_realism.csv
+3b,,comp_l1,scsemi,0.223249,pairs 20,data/sec08_pairs_realism.csv
+3b,,comp_l1,scsemi,0.221315,pairs 40,data/sec08_pairs_realism.csv
+3b,,comp_l1,scsemi,0.217009,pairs all,data/sec08_pairs_realism.csv
+3b,,comp_l1,lora,0.171451,pairs 5,data/sec08_pairs_realism.csv
+3b,,comp_l1,lora,0.187881,pairs 10,data/sec08_pairs_realism.csv
+3b,,comp_l1,lora,0.172324,pairs 20,data/sec08_pairs_realism.csv
+3b,,comp_l1,lora,0.171385,pairs 40,data/sec08_pairs_realism.csv
+3b,,comp_l1,lora,0.161729,pairs all,data/sec08_pairs_realism.csv
+3b,,coverage,scsemi,0.0381931,pairs 5,data/sec08_pairs_realism.csv
+3b,,coverage,scsemi,0.0380062,pairs 10,data/sec08_pairs_realism.csv
+3b,,coverage,scsemi,0.0371963,pairs 20,data/sec08_pairs_realism.csv
+3b,,coverage,scsemi,0.0384424,pairs 40,data/sec08_pairs_realism.csv
+3b,,coverage,scsemi,0.0384424,pairs all,data/sec08_pairs_realism.csv
+3b,,coverage,lora,0.83919,pairs 5,data/sec08_pairs_realism.csv
+3b,,coverage,lora,0.78567,pairs 10,data/sec08_pairs_realism.csv
+3b,,coverage,lora,0.755202,pairs 20,data/sec08_pairs_realism.csv
+3b,,coverage,lora,0.778442,pairs 40,data/sec08_pairs_realism.csv
+3b,,coverage,lora,0.784299,pairs all,data/sec08_pairs_realism.csv
+3b,,nk_fraction_r,scsemi,0.265058,pairs 5,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,scsemi,0.32997,pairs 10,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,scsemi,0.476187,pairs 20,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,scsemi,0.493709,pairs 40,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,scsemi,0.424503,pairs all,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,lora,0.199274,pairs 5,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,lora,0.397169,pairs 10,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,lora,0.564359,pairs 20,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,lora,0.699336,pairs 40,data/sec08_pairs_signal.csv
+3b,,nk_fraction_r,lora,0.701926,pairs all,data/sec08_pairs_signal.csv
+3c,5 donors (mean of 5 draws),comp_l1,copy,0.187144,,data/sec09_scsemi_representative.csv
+3c,5 donors (mean of 5 draws),comp_l1,scsemi,0.232512,,data/sec09_scsemi_representative.csv
+3c,5 donors (mean of 5 draws),comp_l1,lora,0.17556,,data/sec09_scsemi_representative.csv
+3c,,spearman_with_copy_error,scsemi,0.573619,,data/sec09_scsemi_representative.csv
+3c,,spearman_with_copy_error,lora,0.35085,,data/sec09_scsemi_representative.csv

paper-releases/pbisc-diffusion/updates/20261008T125804Z-deck-fig2-3-healthy-fig5-rare/diffusion/dataset/server_1/model8/presentations/2026-09-30--paper-summary--r00/data/fig23_healthy_slide_text.json

@@ -0,0 +1,225 @@
+{
+ "section": "fig23-healthy",
+ "scripts": [
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/tools/fig23_healthy.py"
+ ],
+ "generated_from": "tools/fig23_healthy.py (rerun to refresh; do not edit by hand)",
+ "slides": [
+  {
+   "title": "Healthy cohort: LoRA cells cover the real ones",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig2_healthy_cells.png"
+   ],
+   "keywords": [
+    "5 donors: coverage 0.19 → 0.79",
+    "Precision 0.95; composition L1 0.18",
+    "5-fold: coverage 0.78, L1 0.16"
+   ],
+   "footnote_short": "ImMicro, 107 healthy donors. 5 donors: mean of 5 draws (dots); 5-fold CV shown separately.",
+   "footnote": "ImMicro, 107 healthy donors (no disease metric on this slide). 5 donors: LoRA-5 fine-tuned on 5 paired donors, tested on the other 102, 5 draws (dots, bar = mean). 5-fold CV: every donor generated by the fold model that never trained on it (pooled call), reported separately. Coverage / precision: k = 10 nearest-neighbour balls on held-out real cells in the scorer's PCA-50 (Kynkäänniemi 2019; Naeem 2020); composition L1 over six scANVI types. Values: coverage 5 donors Zero-shot, real bulk 0.190, Zero-shot + calibration 0.535, PBISC LoRA 0.792; 5-fold Zero-shot, real bulk 0.192, Zero-shot + calibration 0.527, sc-only fine-tune (+ cal.) 0.623, PBISC LoRA 0.784; precision 5 donors Zero-shot, real bulk 0.677, Zero-shot + calibration 0.904, PBISC LoRA 0.952; 5-fold Zero-shot, real bulk 0.680, Zero-shot + calibration 0.905, sc-only fine-tune (+ cal.) 0.805, PBISC LoRA 0.924; comp_l1 5 donors Zero-shot, real bulk 0.445, Zero-shot + calibration 0.203, PBISC LoRA 0.176; 5-fold Zero-shot, real bulk 0.455, Zero-shot + calibration 0.199, sc-only fine-tune (+ cal.) 0.240, PBISC LoRA 0.162. Sources: data/sec09_fewpair_cells.csv, data/sec07_ft_modes_accuracy.csv.",
+   "refs": [
+    "Kynkäänniemi 2019, NeurIPS",
+    "Naeem 2020, ICML"
+   ],
+   "refs_full": [
+    "Kynkäänniemi et al. Improved precision and recall metric for assessing generative models. NeurIPS 2019",
+    "Naeem et al. Reliable fidelity and diversity metrics for generative models. ICML 2020"
+   ],
+   "numbers": [
+    {
+     "value": "5 donors (mean of 5 draws) coverage zs_raw 0.19; 5 donors (mean of 5 draws) coverage zs_cal 0.5352; 5 donors (mean of 5 draws) coverage lora 0.7925; 5-fold pooled coverage zs_raw 0.1918; 5-fold pooled coverage zs_cal 0.5272; 5-fold pooled coverage sconly_cal 0.6233; 5-fold pooled coverage lora 0.7843; 5 donors (mean of 5 draws) precision zs_raw 0.6772; 5 donors (mean of 5 draws) precision zs_cal 0.9037; 5 donors (mean of 5 draws) precision lora 0.9521; 5-fold pooled precision zs_raw 0.6804; 5-fold pooled precision zs_cal 0.905; 5-fold pooled precision sconly_cal 0.8047; 5-fold pooled precision lora 0.9241; 5 donors (mean of 5 draws) comp_l1 zs_raw 0.4451; 5 donors (mean of 5 draws) comp_l1 zs_cal 0.2028; 5 donors (mean of 5 draws) comp_l1 lora 0.1756; 5-fold pooled comp_l1 zs_raw 0.4549; 5-fold pooled comp_l1 zs_cal 0.1985; 5-fold pooled comp_l1 sconly_cal 0.2403; 5-fold pooled comp_l1 lora 0.1617",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy cohort: realism beyond precision/coverage",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig2_healthy_realism.png"
+   ],
+   "keywords": [
+    "Every metric: LoRA best of the PBISC versions",
+    "E_N 1.5 vs zero-shot 7.2 (5 donors)",
+    "Classifier AUC 0.94: still separable"
+   ],
+   "footnote_short": "ImMicro, 107 healthy donors. Dashed = real vs real cells of the same donors.",
+   "footnote": "ImMicro. Classifier two-sample test (kNN, 5-fold CV ROC AUC; 0.5 = indistinguishable; Lopez-Paz & Oquab 2017), MMD² (RBF, median bandwidth; Gretton 2012) and scSemiProfiler's E_N (Wang 2024), all on the scorer's cells and embedding. Dashed: real vs real (held-out cells of the same donors). 5 donors: mean of 5 draws (dots); 5-fold reported separately. Source: data/sec09_extra_fewpair.csv, data/sec09_extra_fivefold.csv.",
+   "refs": [
+    "Lopez-Paz 2017, ICLR",
+    "Gretton 2012, JMLR"
+   ],
+   "refs_full": [
+    "Lopez-Paz & Oquab. Revisiting classifier two-sample tests. ICLR 2017",
+    "Gretton et al. A kernel two-sample test. JMLR 13:723-773 (2012)"
+   ],
+   "numbers": [
+    {
+     "value": "5 donors (mean of 5 draws) c2st_knn_auc zs_raw 0.9966; 5 donors (mean of 5 draws) c2st_knn_auc zs_cal 0.9732; 5 donors (mean of 5 draws) c2st_knn_auc lora 0.9427; 5-fold pooled c2st_knn_auc zs_raw 0.9964; 5-fold pooled c2st_knn_auc zs_cal 0.9728; 5-fold pooled c2st_knn_auc sconly_cal 0.9524; 5-fold pooled c2st_knn_auc lora 0.9409; 5 donors (mean of 5 draws) mmd2_bw1 zs_raw 0.1026; 5 donors (mean of 5 draws) mmd2_bw1 zs_cal 0.04304; 5 donors (mean of 5 draws) mmd2_bw1 lora 0.02308; 5-fold pooled mmd2_bw1 zs_raw 0.1019; 5-fold pooled mmd2_bw1 zs_cal 0.04253; 5-fold pooled mmd2_bw1 sconly_cal 0.03419; 5-fold pooled mmd2_bw1 lora 0.0264; 5 donors (mean of 5 draws) en_all_sq zs_raw 7.236; 5 donors (mean of 5 draws) en_all_sq zs_cal 2.855; 5 donors (mean of 5 draws) en_all_sq lora 1.547; 5-fold pooled en_all_sq zs_raw 4.832; 5-fold pooled en_all_sq zs_cal 2.263; 5-fold pooled en_all_sq sconly_cal 1.767; 5-fold pooled en_all_sq lora 1.56",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy cohort: full vs LoRA vs condition encoder",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig2_healthy_modes.png"
+   ],
+   "keywords": [
+    "LoRA ≈ full fine-tune with 42× fewer weights",
+    "LoRA coverage 0.78 vs full 0.70 (5-fold)",
+    "Condition encoder alone falls short"
+   ],
+   "footnote_short": "ImMicro, 107 healthy donors; cond.-encoder-only ran on fold 0 (22 donors) only.",
+   "footnote": "ImMicro. Full fine-tune trains all 54.2 M weights; LoRA r16 1.30 M; condition-encoder-only 9.48 M (fold 0 pilot only). Values: pooled Full fine-tune: L1 0.157, coverage 0.695, precision 0.890; pooled PBISC LoRA: L1 0.162, coverage 0.784, precision 0.924; fold0 Full fine-tune: L1 0.147, coverage 0.841, precision 0.987; fold0 PBISC LoRA: L1 0.153, coverage 0.915, precision 0.992; fold0 Cond.-encoder-only: L1 0.204, coverage 0.728, precision 0.979. Source: data/sec07_ft_modes_accuracy.csv, data/sec07_ft_modes_compute.csv.",
+   "refs": [
+    "Hu 2022, ICLR"
+   ],
+   "refs_full": [
+    "Hu et al. LoRA: Low-Rank Adaptation of Large Language Models. ICLR 2022"
+   ],
+   "numbers": [
+    {
+     "value": "pooled comp_l1 full 0.1572; pooled comp_l1 lora 0.1617; fold0 comp_l1 full 0.147; fold0 comp_l1 lora 0.1529; fold0 comp_l1 condenc 0.2042; pooled coverage full 0.6954; pooled coverage lora 0.7843; fold0 coverage full 0.8412; fold0 coverage lora 0.9148; fold0 coverage condenc 0.7285; pooled precision full 0.8895; pooled precision lora 0.9241; fold0 precision full 0.987; fold0 precision lora 0.9915; fold0 precision condenc 0.9794;  trainable_M full 54.19;  trainable_M lora 1.296;  trainable_M condenc 9.483",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy cohort: how many pairs",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig2_healthy_pairs.png"
+   ],
+   "keywords": [
+    "5 pairs: coverage 0.84 (zero-shot 0.19)",
+    "Donor NK fraction r 0.20 → 0.70 with more pairs",
+    "5 pairs stop early, near 3,000 steps"
+   ],
+   "footnote_short": "ImMicro, 107 donors, 5-fold CV pooled at each pair count. 0 = no pairs.",
+   "footnote": "ImMicro, donor-level 5-fold CV, pooled scoring (107 donors); x = LoRA training pairs per fold (the last point is every training donor of the fold, 78–79). Calibration fitted on exactly the pairs the LoRA point saw. Selected step = early-stopping step on 7 inner-validation pairs (cap 20,000). Values: coverage LoRA 0.84 / 0.79 / 0.76 / 0.78 / 0.78; NK fraction r LoRA 0.20 / 0.40 / 0.56 / 0.70 / 0.70 at 5 / 10 / 20 / 40 / all pairs. Source: data/sec08_pairs_realism.csv, data/sec08_pairs_signal.csv, data/sec08_selected_steps_per_fold.csv.",
+   "refs": [
+    "Kynkäänniemi 2019, NeurIPS",
+    "Naeem 2020, ICML"
+   ],
+   "refs_full": [
+    "Kynkäänniemi et al. Improved precision and recall metric for assessing generative models. NeurIPS 2019",
+    "Naeem et al. Reliable fidelity and diversity metrics for generative models. ICML 2020"
+   ],
+   "numbers": [
+    {
+     "value": "pairs 0 comp_l1 zero_shot 0.4549; pairs 5 comp_l1 zs_cal_budget 0.1916; pairs 10 comp_l1 zs_cal_budget 0.1996; pairs 20 comp_l1 zs_cal_budget 0.1911; pairs 40 comp_l1 zs_cal_budget 0.196; pairs all comp_l1 zs_cal_budget 0.1985; pairs 5 comp_l1 lora 0.1715; pairs 10 comp_l1 lora 0.1879; pairs 20 comp_l1 lora 0.1723; pairs 40 comp_l1 lora 0.1714; pairs all comp_l1 lora 0.1617; pairs 0 coverage zero_shot 0.1918; pairs 5 coverage zs_cal_budget 0.527; pairs 10 coverage zs_cal_budget 0.5287; pairs 20 coverage zs_cal_budget 0.5287; pairs 40 coverage zs_cal_budget 0.5224; pairs all coverage zs_cal_budget 0.5272; pairs 5 coverage lora 0.8392; pairs 10 coverage lora 0.7857; pairs 20 coverage lora 0.7552; pairs 40 coverage lora 0.7784; pairs all coverage lora 0.7843; pairs 0 nk_fraction_r zero_shot 0.4939; pairs 5 nk_fraction_r zs_cal_budget 0.5019; pairs 10 nk_fraction_r zs_cal_budget 0.515; pairs 20 nk_fraction_r zs_cal_budget 0.5251; pairs 40 nk_fraction_r zs_cal_budget 0.5; pairs all nk_fraction_r zs_cal_budget 0.5004; pairs 5 nk_fraction_r lora 0.1993; pairs 10 nk_fraction_r lora 0.3972; pairs 20 nk_fraction_r lora 0.5644; pairs 40 nk_fraction_r lora 0.6993; pairs all nk_fraction_r lora 0.7019; pairs 5 selected_step_median_k lora 3.25; pairs 10 selected_step_median_k lora 5.75; pairs 20 selected_step_median_k lora 19.5; pairs 40 selected_step_median_k lora 20; pairs all selected_step_median_k lora 20",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy cohort: LoRA rank and K",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig2_healthy_rank.png"
+   ],
+   "keywords": [
+    "r64 vs r16: coverage 0.78 → 0.82",
+    "r4 vs r16: L1 0.162 → 0.186",
+    "Multi-K, recipes: no gain; kept r16, K 1,000"
+   ],
+   "footnote_short": "ImMicro, 107 donors, 5-fold CV pooled. Open symbols: K choices with every training pair.",
+   "footnote": "ImMicro, 5-fold CV pooled. LoRA rank 4 / 16 / 64 at 5, 20 and all training pairs; multi-K (K = 250–4,000 conditions) and half-batch recipes with every training pair. Kept: r = 16, K = 1,000. Source: data/sec07_rank_sweep.csv, data/sec07_k_aug.csv.",
+   "refs": [
+    "Hu 2022, ICLR"
+   ],
+   "refs_full": [
+    "Hu et al. LoRA: Low-Rank Adaptation of Large Language Models. ICLR 2022"
+   ],
+   "numbers": [
+    {
+     "value": "pairs 5 comp_l1 lora_r4 0.1622; pairs 20 comp_l1 lora_r4 0.171; pairs all comp_l1 lora_r4 0.1858; pairs 5 comp_l1 lora_r16 0.1715; pairs 20 comp_l1 lora_r16 0.1723; pairs all comp_l1 lora_r16 0.1617; pairs 5 comp_l1 lora_r64 0.1765; pairs 20 comp_l1 lora_r64 0.1717; pairs all comp_l1 lora_r64 0.161; pairs all comp_l1 lora_multik__raw 0.1678; pairs all comp_l1 lora_recipe__raw 0.1609; pairs 5 coverage lora_r4 0.7891; pairs 20 coverage lora_r4 0.715; pairs all coverage lora_r4 0.7123; pairs 5 coverage lora_r16 0.8392; pairs 20 coverage lora_r16 0.7552; pairs all coverage lora_r16 0.7843; pairs 5 coverage lora_r64 0.8473; pairs 20 coverage lora_r64 0.7937; pairs all coverage lora_r64 0.8159; pairs all coverage lora_multik__raw 0.7748; pairs all coverage lora_recipe__raw 0.7655; pairs 5 precision lora_r4 0.9369; pairs 20 precision lora_r4 0.9247; pairs all precision lora_r4 0.9333; pairs 5 precision lora_r16 0.9463; pairs 20 precision lora_r16 0.9204; pairs all precision lora_r16 0.9241; pairs 5 precision lora_r64 0.9455; pairs 20 precision lora_r64 0.9053; pairs all precision lora_r64 0.9044; pairs all precision lora_multik__raw 0.9284; pairs all precision lora_recipe__raw 0.933",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy donors, 5 pairs: LoRA-5 vs scSemiProfiler-5",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig3_healthy_fewpair.png"
+   ],
+   "keywords": [
+    "LoRA-5 ahead on 6 of 6 metrics",
+    "Coverage 0.79 vs 0.04",
+    "E_N 1.5 vs 3.6 (scSemiProfiler's own metric)"
+   ],
+   "footnote_short": "ImMicro, 107 healthy donors; same 5 donors for both methods, 5 draws (dots).",
+   "footnote": "Main comparison on healthy donors: per draw, LoRA-5 and scSemiProfiler get the same 5 paired donors (scSemiProfiler: as its representatives) and are tested on the other 102 from their real bulk; 5 draws. Zero-shot (no pairs) shown for reference. Dashed: real vs real cells. Values (LoRA-5 / scSemiProfiler-5): coverage 0.792 / 0.036; precision 0.952 / 0.518; comp_l1 0.176 / 0.233; c2st_knn_auc 0.943 / 0.999; mmd2_bw1 0.023 / 0.186; en_all_sq 1.547 / 3.649. Source: data/sec09_fewpair_cells.csv, data/sec09_extra_fewpair.csv.",
+   "refs": [
+    "Wang 2024, Nat Commun",
+    "Lopez-Paz 2017, ICLR"
+   ],
+   "refs_full": [
+    "Wang et al. scSemiProfiler: advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning. Nat Commun 15:5989 (2024). doi:10.1038/s41467-024-50150-1",
+    "Lopez-Paz & Oquab. Revisiting classifier two-sample tests. ICLR 2017"
+   ],
+   "numbers": [
+    {
+     "value": "5 donors (mean of 5 draws) coverage zs_raw 0.19; 5 donors (mean of 5 draws) coverage scsemi 0.03583; 5 donors (mean of 5 draws) coverage lora 0.7925; 5 donors (mean of 5 draws) precision zs_raw 0.6772; 5 donors (mean of 5 draws) precision scsemi 0.518; 5 donors (mean of 5 draws) precision lora 0.9521; 5 donors (mean of 5 draws) comp_l1 zs_raw 0.4451; 5 donors (mean of 5 draws) comp_l1 scsemi 0.2325; 5 donors (mean of 5 draws) comp_l1 lora 0.1756; 5 donors (mean of 5 draws) c2st_knn_auc zs_raw 0.9966; 5 donors (mean of 5 draws) c2st_knn_auc scsemi 0.9988; 5 donors (mean of 5 draws) c2st_knn_auc lora 0.9427; 5 donors (mean of 5 draws) mmd2_bw1 zs_raw 0.1026; 5 donors (mean of 5 draws) mmd2_bw1 scsemi 0.1865; 5 donors (mean of 5 draws) mmd2_bw1 lora 0.02308; 5 donors (mean of 5 draws) en_all_sq zs_raw 7.236; 5 donors (mean of 5 draws) en_all_sq scsemi 3.649; 5 donors (mean of 5 draws) en_all_sq lora 1.547",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy donors: the same pairs, 5 to all",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig3_healthy_pairs.png"
+   ],
+   "keywords": [
+    "Coverage at every n: LoRA 0.76–0.84, scSemiProfiler 0.04",
+    "Composition L1 lower for LoRA at every n",
+    "5-fold: LoRA 0.16 vs 0.22 L1"
+   ],
+   "footnote_short": "ImMicro, 107 donors, 5-fold CV design; scSemiProfiler gets exactly LoRA's pairs.",
+   "footnote": "ImMicro, donor-level 5-fold CV pooled at each pair count: for every fold, scSemiProfiler's representatives are exactly the n pairs LoRA trained on (plus the inner-validation pairs); 'all' (open symbols, right of the dotted line) = every training donor of the fold, i.e. the 5-fold result, reported separately from the 5-pair comparison. Source: data/sec08_pairs_realism.csv, data/sec08_pairs_signal.csv, data/sec09_same_pairs.csv.",
+   "refs": [
+    "Wang 2024, Nat Commun"
+   ],
+   "refs_full": [
+    "Wang et al. scSemiProfiler: advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning. Nat Commun 15:5989 (2024). doi:10.1038/s41467-024-50150-1"
+   ],
+   "numbers": [
+    {
+     "value": "pairs 5 comp_l1 scsemi 0.2184; pairs 10 comp_l1 scsemi 0.2269; pairs 20 comp_l1 scsemi 0.2232; pairs 40 comp_l1 scsemi 0.2213; pairs all comp_l1 scsemi 0.217; pairs 5 comp_l1 lora 0.1715; pairs 10 comp_l1 lora 0.1879; pairs 20 comp_l1 lora 0.1723; pairs 40 comp_l1 lora 0.1714; pairs all comp_l1 lora 0.1617; pairs 5 coverage scsemi 0.03819; pairs 10 coverage scsemi 0.03801; pairs 20 coverage scsemi 0.0372; pairs 40 coverage scsemi 0.03844; pairs all coverage scsemi 0.03844; pairs 5 coverage lora 0.8392; pairs 10 coverage lora 0.7857; pairs 20 coverage lora 0.7552; pairs 40 coverage lora 0.7784; pairs all coverage lora 0.7843; pairs 5 nk_fraction_r scsemi 0.2651; pairs 10 nk_fraction_r scsemi 0.33; pairs 20 nk_fraction_r scsemi 0.4762; pairs 40 nk_fraction_r scsemi 0.4937; pairs all nk_fraction_r scsemi 0.4245; pairs 5 nk_fraction_r lora 0.1993; pairs 10 nk_fraction_r lora 0.3972; pairs 20 nk_fraction_r lora 0.5644; pairs 40 nk_fraction_r lora 0.6993; pairs all nk_fraction_r lora 0.7019",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  },
+  {
+   "title": "Healthy donors: scSemiProfiler copies its representative",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig3_healthy_copy.png"
+   ],
+   "keywords": [
+    "scSemiProfiler 0.233 vs copying 0.187 (L1)",
+    "Its error tracks the copy's: ρ 0.57",
+    "LoRA-5 below the copy: 0.176"
+   ],
+   "footnote_short": "ImMicro, 102 test donors per draw, 5 draws. Copy = the assigned representative's composition.",
+   "footnote": "ImMicro, 5 donors. scSemiProfiler assigns each test sample one representative; 'copy' uses that representative's observed composition as the prediction. Right: Spearman over test samples between each method's composition error and the copy's error. Source: data/sec09_scsemi_representative.csv (scsemi/analysis/representative_dependence_20261002).",
+   "refs": [
+    "Wang 2024, Nat Commun"
+   ],
+   "refs_full": [
+    "Wang et al. scSemiProfiler: advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning. Nat Commun 15:5989 (2024). doi:10.1038/s41467-024-50150-1"
+   ],
+   "numbers": [
+    {
+     "value": "5 donors (mean of 5 draws) comp_l1 copy 0.1871; 5 donors (mean of 5 draws) comp_l1 scsemi 0.2325; 5 donors (mean of 5 draws) comp_l1 lora 0.1756;  spearman_with_copy_error scsemi 0.5736;  spearman_with_copy_error lora 0.3509",
+     "source": "data/fig23_healthy.csv"
+    }
+   ]
+  }
+ ]
+}

paper-releases/pbisc-diffusion/updates/20261008T125804Z-deck-fig2-3-healthy-fig5-rare/diffusion/dataset/server_1/model8/presentations/2026-09-30--paper-summary--r00/data/fig5_rare_states.csv

@@ -0,0 +1,449 @@
+dataset,state,arm,log2_ratio,spearman,auroc,direction,design
+giroux2022,C1Q-high monocyte (reference),lora5,-2.6404,-0.012152,0.48311,0.6,5 donors (mean of 5 draws)
+giroux2022,C1Q-high monocyte (reference),scsemi5,-3.6501,-0.14423,0.42467,0,5 donors (mean of 5 draws)
+giroux2022,C1Q-high monocyte (reference),zs_cal,-2.563,-0.09803,0.436,0.4,5 donors (mean of 5 draws)
+giroux2022,C1Q-high monocyte (reference),zs_raw,-2.2749,-0.23164,0.39867,0,5 donors (mean of 5 draws)
+giroux2022,Cycling T/NK,lora5,-1.3087,0.43795,0.694,1,5 donors (mean of 5 draws)
+giroux2022,Cycling T/NK,scsemi5,-3.5999,0.33924,0.58278,0.8,5 donors (mean of 5 draws)
+giroux2022,Cycling T/NK,zs_cal,-1.9449,0.27444,0.62644,0.8,5 donors (mean of 5 draws)
+giroux2022,Cycling T/NK,zs_raw,-1.2512,0.38518,0.62867,1,5 donors (mean of 5 draws)
+giroux2022,Cycling activated T (CD38/HLA-DR),lora5,-2.5882,0.38932,0.684,0.8,5 donors (mean of 5 draws)
+giroux2022,Cycling activated T (CD38/HLA-DR),scsemi5,-1.854,0.48112,0.68578,1,5 donors (mean of 5 draws)
+giroux2022,Cycling activated T (CD38/HLA-DR),zs_cal,-3.3551,0.057451,0.44389,1,5 donors (mean of 5 draws)
+giroux2022,Cycling activated T (CD38/HLA-DR),zs_raw,-2.638,0.3025,0.65878,1,5 donors (mean of 5 draws)
+giroux2022,Cycling monocyte (Ye 2026),lora5,-3.2484,0.12073,0.54922,0.6,5 donors (mean of 5 draws)
+giroux2022,Cycling monocyte (Ye 2026),scsemi5,-3.2112,-0.20694,0.43467,0.4,5 donors (mean of 5 draws)
+giroux2022,Cycling monocyte (Ye 2026),zs_cal,-4.5199,0.0029991,0.46089,0.4,5 donors (mean of 5 draws)
+giroux2022,Cycling monocyte (Ye 2026),zs_raw,-5.0497,0.049639,0.51078,0.4,5 donors (mean of 5 draws)
+giroux2022,Cytotoxic CD4 T,lora5,-0.49456,0.4228,0.77222,1,5 donors (mean of 5 draws)
+giroux2022,Cytotoxic CD4 T,scsemi5,3.7826,0.4332,0.77467,1,5 donors (mean of 5 draws)
+giroux2022,Cytotoxic CD4 T,zs_cal,0.93121,0.33488,0.71467,0.6,5 donors (mean of 5 draws)
+giroux2022,Cytotoxic CD4 T,zs_raw,-0.80043,0.25661,0.67978,0.6,5 donors (mean of 5 draws)
+giroux2022,DN2 / ABC B,lora5,-1.9314,-0.0076739,0.46556,1,5 donors (mean of 5 draws)
+giroux2022,DN2 / ABC B,scsemi5,,,0.5,0,5 donors (mean of 5 draws)
+giroux2022,DN2 / ABC B,zs_cal,-1.712,-0.020185,0.44967,0,5 donors (mean of 5 draws)
+giroux2022,DN2 / ABC B,zs_raw,-0.71825,0.31321,0.72667,0.6,5 donors (mean of 5 draws)
+giroux2022,Granulocyte-like (LDG),lora5,-6.0304,0.2767,0.6,0.6,5 donors (mean of 5 draws)
+giroux2022,Granulocyte-like (LDG),scsemi5,,,0.5,0,5 donors (mean of 5 draws)
+giroux2022,Granulocyte-like (LDG),zs_cal,-3.6865,0.42869,0.658,0.6,5 donors (mean of 5 draws)
+giroux2022,Granulocyte-like (LDG),zs_raw,-2.2949,0.61894,0.745,0.8,5 donors (mean of 5 draws)
+giroux2022,HSPC,lora5,-1.6448,0.06297,0.54411,0.6,5 donors (mean of 5 draws)
+giroux2022,HSPC,scsemi5,-3.4927,-0.17408,0.48,0,5 donors (mean of 5 draws)
+giroux2022,HSPC,zs_cal,-1.2527,-0.16205,0.41189,0.4,5 donors (mean of 5 draws)
+giroux2022,HSPC,zs_raw,-0.061678,-0.21312,0.39689,0.8,5 donors (mean of 5 draws)
+giroux2022,ISG-high T,lora5,-0.86852,0.8469,0.92911,1,5 donors (mean of 5 draws)
+giroux2022,ISG-high T,scsemi5,2.6225,0.76724,0.77,1,5 donors (mean of 5 draws)
+giroux2022,ISG-high T,zs_cal,0.1885,0.83427,0.912,1,5 donors (mean of 5 draws)
+giroux2022,ISG-high T,zs_raw,-0.5941,0.73226,0.90089,1,5 donors (mean of 5 draws)
+giroux2022,ISG-high monocyte (positive control),lora5,-0.15917,0.72998,0.85089,1,5 donors (mean of 5 draws)
+giroux2022,ISG-high monocyte (positive control),scsemi5,0.75684,0.65568,0.69333,0.8,5 donors (mean of 5 draws)
+giroux2022,ISG-high monocyte (positive control),zs_cal,0.71977,0.72443,0.82511,1,5 donors (mean of 5 draws)
+giroux2022,ISG-high monocyte (positive control),zs_raw,0.3143,0.80601,0.86511,0.8,5 donors (mean of 5 draws)
+giroux2022,MS1 monocyte (IL1R2+),lora5,-2.2748,0.1478,0.50333,0.8,5 donors (mean of 5 draws)
+giroux2022,MS1 monocyte (IL1R2+),scsemi5,,,0.5,0,5 donors (mean of 5 draws)
+giroux2022,MS1 monocyte (IL1R2+),zs_cal,2.2914,0.039838,0.528,0.8,5 donors (mean of 5 draws)
+giroux2022,MS1 monocyte (IL1R2+),zs_raw,0.31939,0.025603,0.50267,0.6,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (label),lora5,-0.91864,0.4396,0.79211,0.6,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (label),scsemi5,-3.7311,-0.06005,0.50789,1,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (label),zs_cal,-0.9373,0.36945,0.72756,0.4,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (label),zs_raw,-0.93464,-0.14304,0.48678,0.2,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (markers),lora5,-2.6619,0.17186,0.63278,0.4,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (markers),scsemi5,0.43243,0.43393,0.73467,1,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (markers),zs_cal,-2.6116,0.20474,0.64667,0.4,5 donors (mean of 5 draws)
+giroux2022,Plasmablast (markers),zs_raw,-1.9185,0.15029,0.589,0,5 donors (mean of 5 draws)
+giroux2022,Proliferating T (label),lora5,-0.41192,0.61193,0.74933,0.8,5 donors (mean of 5 draws)
+giroux2022,Proliferating T (label),scsemi5,2.5503,0.622,0.74444,1,5 donors (mean of 5 draws)
+giroux2022,Proliferating T (label),zs_cal,-0.055869,0.5581,0.821,1,5 donors (mean of 5 draws)
+giroux2022,Proliferating T (label),zs_raw,-0.36094,0.49669,0.71356,1,5 donors (mean of 5 draws)
+imperial_eskd,C1Q-high monocyte (reference),lora5,-2.5268,0.074885,0.54605,0.8,5 donors (mean of 5 draws)
+imperial_eskd,C1Q-high monocyte (reference),scsemi5,-1.9428,0.17602,0.59084,1,5 donors (mean of 5 draws)
+imperial_eskd,C1Q-high monocyte (reference),zs_cal,-2.5959,0.19024,0.61771,1,5 donors (mean of 5 draws)
+imperial_eskd,C1Q-high monocyte (reference),zs_raw,-4.2642,0.16821,0.57267,0.4,5 donors (mean of 5 draws)
+imperial_eskd,Cycling T/NK,lora5,-1.5941,0.23578,0.61006,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling T/NK,scsemi5,-5.219,0.075909,0.51448,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling T/NK,zs_cal,1.6569,0.33661,0.68745,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling T/NK,zs_raw,1.6474,0.17797,0.57454,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling activated T (CD38/HLA-DR),lora5,-3.065,0.079376,0.53833,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling activated T (CD38/HLA-DR),scsemi5,-6.806,-0.065897,0.48248,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling activated T (CD38/HLA-DR),zs_cal,-0.46332,0.12701,0.55668,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling activated T (CD38/HLA-DR),zs_raw,-0.642,0.26082,0.62366,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling monocyte (Ye 2026),lora5,-2.9764,0.12464,0.54596,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling monocyte (Ye 2026),scsemi5,-6.5059,0.002497,0.50292,0.8,5 donors (mean of 5 draws)
+imperial_eskd,Cycling monocyte (Ye 2026),zs_cal,-2.071,0.29831,0.60257,1,5 donors (mean of 5 draws)
+imperial_eskd,Cycling monocyte (Ye 2026),zs_raw,-3.0721,-0.012999,0.45779,1,5 donors (mean of 5 draws)
+imperial_eskd,Cytotoxic CD4 T,lora5,1.5757,0.19447,0.60248,0.6,5 donors (mean of 5 draws)
+imperial_eskd,Cytotoxic CD4 T,scsemi5,2.0968,0.025512,0.51206,1,5 donors (mean of 5 draws)
+imperial_eskd,Cytotoxic CD4 T,zs_cal,2.1449,0.18284,0.60292,0,5 donors (mean of 5 draws)
+imperial_eskd,Cytotoxic CD4 T,zs_raw,-0.11863,0.11066,0.54365,0,5 donors (mean of 5 draws)
+imperial_eskd,DN2 / ABC B,lora5,-1.242,0.045417,0.52668,0.6,5 donors (mean of 5 draws)
+imperial_eskd,DN2 / ABC B,scsemi5,-5.5876,0.019939,0.4978,1,5 donors (mean of 5 draws)
+imperial_eskd,DN2 / ABC B,zs_cal,-0.98847,0.036512,0.52235,0.2,5 donors (mean of 5 draws)
+imperial_eskd,DN2 / ABC B,zs_raw,0.7528,0.26841,0.69335,1,5 donors (mean of 5 draws)
+imperial_eskd,Granulocyte-like (LDG),lora5,-5.8088,0.12132,0.52185,0.2,5 donors (mean of 5 draws)
+imperial_eskd,Granulocyte-like (LDG),scsemi5,-8.6877,0.076786,0.50712,0.2,5 donors (mean of 5 draws)
+imperial_eskd,Granulocyte-like (LDG),zs_cal,-3.7011,0.16074,0.57652,0,5 donors (mean of 5 draws)
+imperial_eskd,Granulocyte-like (LDG),zs_raw,-0.36266,0.23437,0.62665,0,5 donors (mean of 5 draws)
+imperial_eskd,HSPC,lora5,0.35038,0.15173,0.58146,0.8,5 donors (mean of 5 draws)
+imperial_eskd,HSPC,scsemi5,-5.4287,0.023071,0.5072,1,5 donors (mean of 5 draws)
+imperial_eskd,HSPC,zs_cal,0.015592,0.16357,0.58055,1,5 donors (mean of 5 draws)
+imperial_eskd,HSPC,zs_raw,-0.92453,0.039978,0.5544,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high T,lora5,-0.73614,0.78012,0.90403,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high T,scsemi5,-1.1842,0.72048,0.78139,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high T,zs_cal,-0.56073,0.83044,0.92781,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high T,zs_raw,-1.0601,0.7209,0.88099,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high monocyte (positive control),lora5,-0.024345,0.81582,0.94203,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high monocyte (positive control),scsemi5,-0.61931,0.76751,0.83652,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high monocyte (positive control),zs_cal,0.23791,0.84059,0.94953,1,5 donors (mean of 5 draws)
+imperial_eskd,ISG-high monocyte (positive control),zs_raw,0.19971,0.8243,0.94582,1,5 donors (mean of 5 draws)
+imperial_eskd,MS1 monocyte (IL1R2+),lora5,-1.4977,0.48356,0.6606,1,5 donors (mean of 5 draws)
+imperial_eskd,MS1 monocyte (IL1R2+),scsemi5,-4.317,0.25148,0.51595,0.8,5 donors (mean of 5 draws)
+imperial_eskd,MS1 monocyte (IL1R2+),zs_cal,1.3968,0.54708,0.75614,1,5 donors (mean of 5 draws)
+imperial_eskd,MS1 monocyte (IL1R2+),zs_raw,-0.50803,0.48336,0.73743,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (label),lora5,-0.53716,0.30927,0.64917,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (label),scsemi5,-1.5114,0.29149,0.63487,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (label),zs_cal,-1.3827,0.40127,0.67384,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (label),zs_raw,-2.1512,0.17509,0.55031,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (markers),lora5,-0.93358,0.34253,0.64392,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (markers),scsemi5,-1.9505,0.22889,0.60406,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (markers),zs_cal,-2.0182,0.41191,0.66208,1,5 donors (mean of 5 draws)
+imperial_eskd,Plasmablast (markers),zs_raw,-2.2436,0.32334,0.62821,1,5 donors (mean of 5 draws)
+imperial_eskd,Proliferating T (label),lora5,0.44352,0.48631,0.74718,1,5 donors (mean of 5 draws)
+imperial_eskd,Proliferating T (label),scsemi5,-1.2207,0.24198,0.6267,1,5 donors (mean of 5 draws)
+imperial_eskd,Proliferating T (label),zs_cal,0.67016,0.44478,0.73313,1,5 donors (mean of 5 draws)
+imperial_eskd,Proliferating T (label),zs_raw,1.4435,0.48753,0.73811,1,5 donors (mean of 5 draws)
+ji2025_chili,C1Q-high monocyte (reference),lora5,-1.2799,-0.017944,0.45353,1,5 donors (mean of 5 draws)
+ji2025_chili,C1Q-high monocyte (reference),scsemi5,-3.7782,0.17697,0.53225,0.4,5 donors (mean of 5 draws)
+ji2025_chili,C1Q-high monocyte (reference),zs_cal,-4.1073,0.01102,0.54121,0.6,5 donors (mean of 5 draws)
+ji2025_chili,C1Q-high monocyte (reference),zs_raw,-4.1752,0.2537,0.53495,0.4,5 donors (mean of 5 draws)
+ji2025_chili,Cycling T/NK,lora5,-1.77,0.20095,0.57207,1,5 donors (mean of 5 draws)
+ji2025_chili,Cycling T/NK,scsemi5,-6.0057,0.17264,0.53205,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Cycling T/NK,zs_cal,-1.3861,0.27854,0.61314,1,5 donors (mean of 5 draws)
+ji2025_chili,Cycling T/NK,zs_raw,0.46595,0.36196,0.74526,1,5 donors (mean of 5 draws)
+ji2025_chili,Cycling activated T (CD38/HLA-DR),lora5,-2.9091,0.21057,0.54731,0.8,5 donors (mean of 5 draws)
+ji2025_chili,Cycling activated T (CD38/HLA-DR),scsemi5,-6.7997,0.2744,0.54872,0.8,5 donors (mean of 5 draws)
+ji2025_chili,Cycling activated T (CD38/HLA-DR),zs_cal,-2.784,0.26617,0.61977,1,5 donors (mean of 5 draws)
+ji2025_chili,Cycling activated T (CD38/HLA-DR),zs_raw,-1.101,0.57525,0.80784,1,5 donors (mean of 5 draws)
+ji2025_chili,Cycling monocyte (Ye 2026),lora5,-4.5524,0.071524,0.52991,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Cycling monocyte (Ye 2026),scsemi5,,,0.5,0,5 donors (mean of 5 draws)
+ji2025_chili,Cycling monocyte (Ye 2026),zs_cal,-3.8874,0.082357,0.49455,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Cycling monocyte (Ye 2026),zs_raw,-1.4595,0.19658,0.60197,1,5 donors (mean of 5 draws)
+ji2025_chili,Cytotoxic CD4 T,lora5,0.34576,0.10596,0.53668,0.2,5 donors (mean of 5 draws)
+ji2025_chili,Cytotoxic CD4 T,scsemi5,0.96177,0.15301,0.59526,1,5 donors (mean of 5 draws)
+ji2025_chili,Cytotoxic CD4 T,zs_cal,0.94516,-0.033189,0.50219,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Cytotoxic CD4 T,zs_raw,0.81185,-0.081371,0.45298,0.2,5 donors (mean of 5 draws)
+ji2025_chili,DN2 / ABC B,lora5,-1.5189,0.078677,0.59412,0.2,5 donors (mean of 5 draws)
+ji2025_chili,DN2 / ABC B,scsemi5,,,0.5,0,5 donors (mean of 5 draws)
+ji2025_chili,DN2 / ABC B,zs_cal,-1.4786,0.19776,0.56536,0.6,5 donors (mean of 5 draws)
+ji2025_chili,DN2 / ABC B,zs_raw,0.67853,0.021323,0.49769,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Granulocyte-like (LDG),lora5,-6.4898,0.027918,0.50371,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Granulocyte-like (LDG),scsemi5,-7.3193,-0.067208,0.48526,0.4,5 donors (mean of 5 draws)
+ji2025_chili,Granulocyte-like (LDG),zs_cal,-4.3718,0.13447,0.56684,0.8,5 donors (mean of 5 draws)
+ji2025_chili,Granulocyte-like (LDG),zs_raw,-0.84518,0.0038266,0.47785,0.4,5 donors (mean of 5 draws)
+ji2025_chili,HSPC,lora5,-1.1919,0.16958,0.57731,0.4,5 donors (mean of 5 draws)
+ji2025_chili,HSPC,scsemi5,-6.7517,-0.010771,0.49936,0.2,5 donors (mean of 5 draws)
+ji2025_chili,HSPC,zs_cal,-2.395,0.10895,0.56061,0.2,5 donors (mean of 5 draws)
+ji2025_chili,HSPC,zs_raw,-1.6857,0.55505,0.78962,0.4,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high T,lora5,-1.7612,0.45854,0.6547,1,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high T,scsemi5,-6.5497,0.33994,0.50833,0.2,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high T,zs_cal,-0.56976,0.31567,0.61771,0.8,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high T,zs_raw,3.8752,0.39391,0.66193,1,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high monocyte (positive control),lora5,-1.6284,0.46939,0.77765,1,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high monocyte (positive control),scsemi5,,,0.5,0,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high monocyte (positive control),zs_cal,1.0452,0.35482,0.69081,1,5 donors (mean of 5 draws)
+ji2025_chili,ISG-high monocyte (positive control),zs_raw,3.5183,0.4667,0.74015,1,5 donors (mean of 5 draws)
+ji2025_chili,MS1 monocyte (IL1R2+),lora5,-2.8873,0.52392,0.76844,1,5 donors (mean of 5 draws)
+ji2025_chili,MS1 monocyte (IL1R2+),scsemi5,-7.5061,0.28307,0.60705,0.6,5 donors (mean of 5 draws)
+ji2025_chili,MS1 monocyte (IL1R2+),zs_cal,-6.7996,0.23522,0.58083,1,5 donors (mean of 5 draws)
+ji2025_chili,MS1 monocyte (IL1R2+),zs_raw,-4.3666,0.39153,0.73948,1,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (label),lora5,-0.88561,-0.034929,0.46478,0.4,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (label),scsemi5,-2.5439,0.014897,0.48168,0.4,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (label),zs_cal,-0.58287,0.065111,0.47456,0.2,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (label),zs_raw,0.55194,-0.29478,0.31307,0,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (markers),lora5,-1.2353,0.023444,0.48088,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (markers),scsemi5,-2.7516,0.13267,0.54933,0.2,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (markers),zs_cal,-1.1607,0.1064,0.49114,0,5 donors (mean of 5 draws)
+ji2025_chili,Plasmablast (markers),zs_raw,0.033521,-0.18774,0.41406,0,5 donors (mean of 5 draws)
+ji2025_chili,Proliferating T (label),lora5,-0.65586,0.34095,0.67018,1,5 donors (mean of 5 draws)
+ji2025_chili,Proliferating T (label),scsemi5,-2.6726,0.24416,0.58591,0.6,5 donors (mean of 5 draws)
+ji2025_chili,Proliferating T (label),zs_cal,-0.26394,0.43167,0.71695,1,5 donors (mean of 5 draws)
+ji2025_chili,Proliferating T (label),zs_raw,1.8519,0.33547,0.67553,1,5 donors (mean of 5 draws)
+ye2026_sepsis,C1Q-high monocyte (reference),lora5,-2.8409,0.1882,0.58866,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,C1Q-high monocyte (reference),scsemi5,-1.823,0.22469,0.61508,1,5 donors (mean of 5 draws)
+ye2026_sepsis,C1Q-high monocyte (reference),zs_cal,-3.5349,0.22259,0.62756,0.8,5 donors (mean of 5 draws)
+ye2026_sepsis,C1Q-high monocyte (reference),zs_raw,-5.4147,-0.0028043,0.46974,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling T/NK,lora5,-1.2143,0.21513,0.64148,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling T/NK,scsemi5,-4.7467,0.16851,0.54972,0.4,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling T/NK,zs_cal,-0.31339,0.11086,0.5991,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling T/NK,zs_raw,-0.30656,0.040769,0.55374,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),lora5,-1.9537,0.26887,0.65963,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),scsemi5,-5.3375,0.13218,0.54564,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),zs_cal,-1.1796,0.063948,0.54834,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),zs_raw,-1.4267,0.025108,0.53317,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling monocyte (Ye 2026),lora5,-4.1296,0.24056,0.58596,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling monocyte (Ye 2026),scsemi5,-6.5372,0.065502,0.5135,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling monocyte (Ye 2026),zs_cal,-2.4648,0.37257,0.66884,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Cycling monocyte (Ye 2026),zs_raw,-3.6999,0.36827,0.63386,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Cytotoxic CD4 T,lora5,0.42101,0.57532,0.74861,0.4,5 donors (mean of 5 draws)
+ye2026_sepsis,Cytotoxic CD4 T,scsemi5,0.4298,0.32199,0.67292,0.2,5 donors (mean of 5 draws)
+ye2026_sepsis,Cytotoxic CD4 T,zs_cal,1.193,0.50154,0.72452,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Cytotoxic CD4 T,zs_raw,-1.3942,0.27159,0.58934,0,5 donors (mean of 5 draws)
+ye2026_sepsis,DN2 / ABC B,lora5,-1.5065,0.16145,0.58303,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,DN2 / ABC B,scsemi5,-5.6035,0.033892,0.50325,0.4,5 donors (mean of 5 draws)
+ye2026_sepsis,DN2 / ABC B,zs_cal,-1.9167,0.042635,0.52375,0.2,5 donors (mean of 5 draws)
+ye2026_sepsis,DN2 / ABC B,zs_raw,0.40284,0.27877,0.62327,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,Granulocyte-like (LDG),lora5,-4.6078,0.33723,0.68449,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,Granulocyte-like (LDG),scsemi5,-9.0099,0.17304,0.5241,0.8,5 donors (mean of 5 draws)
+ye2026_sepsis,Granulocyte-like (LDG),zs_cal,-5.136,0.22926,0.59952,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Granulocyte-like (LDG),zs_raw,-2.2287,0.43872,0.72452,1,5 donors (mean of 5 draws)
+ye2026_sepsis,HSPC,lora5,0.52995,0.030248,0.49245,1,5 donors (mean of 5 draws)
+ye2026_sepsis,HSPC,scsemi5,-6.8556,0.08843,0.50789,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,HSPC,zs_cal,2.4591,0.038305,0.47701,1,5 donors (mean of 5 draws)
+ye2026_sepsis,HSPC,zs_raw,-0.8757,0.11692,0.50132,1,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high T,lora5,-0.72835,0.52286,0.72493,1,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high T,scsemi5,-5.421,0.31256,0.53947,0.8,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high T,zs_cal,-0.17526,0.26809,0.55429,0.8,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high T,zs_raw,0.84066,0.35084,0.62472,1,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high monocyte (positive control),lora5,-0.61369,0.55782,0.76178,0.8,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high monocyte (positive control),scsemi5,-4.8699,0.36059,0.55472,0,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high monocyte (positive control),zs_cal,-0.39815,0.42322,0.73089,1,5 donors (mean of 5 draws)
+ye2026_sepsis,ISG-high monocyte (positive control),zs_raw,0.90375,0.44691,0.71468,1,5 donors (mean of 5 draws)
+ye2026_sepsis,MS1 monocyte (IL1R2+),lora5,-3.3332,0.41391,0.69631,1,5 donors (mean of 5 draws)
+ye2026_sepsis,MS1 monocyte (IL1R2+),scsemi5,-7.5412,0.21662,0.5309,1,5 donors (mean of 5 draws)
+ye2026_sepsis,MS1 monocyte (IL1R2+),zs_cal,-1.2426,0.50396,0.73283,1,5 donors (mean of 5 draws)
+ye2026_sepsis,MS1 monocyte (IL1R2+),zs_raw,-3.7862,0.5086,0.74584,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (label),lora5,-1.6494,0.28336,0.64384,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (label),scsemi5,-2.4978,0.31562,0.64702,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (label),zs_cal,-0.42046,0.35749,0.68248,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (label),zs_raw,-1.3406,0.36696,0.68857,1,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (markers),lora5,-2.6808,0.25829,0.62036,0.4,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (markers),scsemi5,-3.4603,0.1625,0.57645,0.4,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (markers),zs_cal,-1.6638,0.42223,0.69037,0.6,5 donors (mean of 5 draws)
+ye2026_sepsis,Plasmablast (markers),zs_raw,-1.774,0.35632,0.63116,0.2,5 donors (mean of 5 draws)
+ye2026_sepsis,Proliferating T (label),lora5,-0.30514,0.28563,0.6662,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Proliferating T (label),scsemi5,-2.2355,0.17617,0.55776,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Proliferating T (label),zs_cal,-0.12543,0.070704,0.54176,0,5 donors (mean of 5 draws)
+ye2026_sepsis,Proliferating T (label),zs_raw,0.98045,0.02976,0.51032,0,5 donors (mean of 5 draws)
+ye2026_sepsis,C1Q-high monocyte (reference),zs__raw,-5.2595,0.15638,0.5818,1,5-fold pooled
+ye2026_sepsis,Cycling T/NK,zs__raw,-0.2839,0.16863,0.61035,0,5-fold pooled
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),zs__raw,-1.4656,0.05262,0.5116,0,5-fold pooled
+ye2026_sepsis,Proliferating T (label),zs__raw,0.97407,-0.018709,0.48215,0,5-fold pooled
+ye2026_sepsis,Plasmablast (label),zs__raw,-1.3742,0.33208,0.67162,1,5-fold pooled
+ye2026_sepsis,Plasmablast (markers),zs__raw,-1.8487,0.38111,0.64039,0,5-fold pooled
+ye2026_sepsis,MS1 monocyte (IL1R2+),zs__raw,-3.6557,0.57012,0.80547,1,5-fold pooled
+ye2026_sepsis,Cycling monocyte (Ye 2026),zs__raw,-3.379,0.18386,0.55651,1,5-fold pooled
+ye2026_sepsis,ISG-high monocyte (positive control),zs__raw,0.84174,0.49779,0.71981,1,5-fold pooled
+ye2026_sepsis,ISG-high T,zs__raw,0.799,0.3979,0.70553,1,5-fold pooled
+ye2026_sepsis,DN2 / ABC B,zs__raw,0.55245,0.11146,0.5809,1,5-fold pooled
+ye2026_sepsis,HSPC,zs__raw,-0.83139,-0.030124,0.47383,1,5-fold pooled
+ye2026_sepsis,Cytotoxic CD4 T,zs__raw,-1.19,0.40328,0.6041,0,5-fold pooled
+ye2026_sepsis,Granulocyte-like (LDG),zs__raw,-2.0936,0.4041,0.73766,1,5-fold pooled
+ye2026_sepsis,C1Q-high monocyte (reference),zs__cal,-3.7934,0.43147,0.74777,1,5-fold pooled
+ye2026_sepsis,Cycling T/NK,zs__cal,-0.67961,0.15863,0.5809,0,5-fold pooled
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),zs__cal,-1.6134,0.05859,0.53123,0,5-fold pooled
+ye2026_sepsis,Proliferating T (label),zs__cal,-0.48445,0.067533,0.53629,0,5-fold pooled
+ye2026_sepsis,Plasmablast (label),zs__cal,-0.46986,0.38137,0.69631,1,5-fold pooled
+ye2026_sepsis,Plasmablast (markers),zs__cal,-1.7517,0.53197,0.76205,1,5-fold pooled
+ye2026_sepsis,MS1 monocyte (IL1R2+),zs__cal,-1.0857,0.60904,0.78911,1,5-fold pooled
+ye2026_sepsis,Cycling monocyte (Ye 2026),zs__cal,-2.599,0.2345,0.61779,1,5-fold pooled
+ye2026_sepsis,ISG-high monocyte (positive control),zs__cal,-0.5186,0.53959,0.7793,1,5-fold pooled
+ye2026_sepsis,ISG-high T,zs__cal,-0.2819,0.45175,0.68055,1,5-fold pooled
+ye2026_sepsis,DN2 / ABC B,zs__cal,-2.0198,-0.084526,0.4298,0,5-fold pooled
+ye2026_sepsis,HSPC,zs__cal,2.0935,0.11366,0.5345,1,5-fold pooled
+ye2026_sepsis,Cytotoxic CD4 T,zs__cal,1.2205,0.51551,0.70613,0,5-fold pooled
+ye2026_sepsis,Granulocyte-like (LDG),zs__cal,-5.2013,0.28962,0.6514,1,5-fold pooled
+ye2026_sepsis,C1Q-high monocyte (reference),scsemi__raw,-0.81433,0.37793,0.78186,1,5-fold pooled
+ye2026_sepsis,Cycling T/NK,scsemi__raw,-2.7638,0.24412,0.57466,1,5-fold pooled
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),scsemi__raw,-3.3321,0.17714,0.54194,1,5-fold pooled
+ye2026_sepsis,Proliferating T (label),scsemi__raw,-1.3128,0.27257,0.61481,1,5-fold pooled
+ye2026_sepsis,Plasmablast (label),scsemi__raw,0.13579,0.42628,0.70167,1,5-fold pooled
+ye2026_sepsis,Plasmablast (markers),scsemi__raw,-0.79,0.36242,0.65675,1,5-fold pooled
+ye2026_sepsis,MS1 monocyte (IL1R2+),scsemi__raw,-3.3289,0.31714,0.61704,1,5-fold pooled
+ye2026_sepsis,Cycling monocyte (Ye 2026),scsemi__raw,-5.6498,0.15622,0.53082,1,5-fold pooled
+ye2026_sepsis,ISG-high monocyte (positive control),scsemi__raw,-4.7455,0.41493,0.57895,0,5-fold pooled
+ye2026_sepsis,ISG-high T,scsemi__raw,-4.7298,0.44141,0.57317,0,5-fold pooled
+ye2026_sepsis,DN2 / ABC B,scsemi__raw,-7.7313,-0.055377,0.4884,1,5-fold pooled
+ye2026_sepsis,HSPC,scsemi__raw,-5.6876,0.094708,0.5122,1,5-fold pooled
+ye2026_sepsis,Cytotoxic CD4 T,scsemi__raw,0.68875,0.35213,0.67341,1,5-fold pooled
+ye2026_sepsis,Granulocyte-like (LDG),scsemi__raw,-3.9998,0.011898,0.53242,1,5-fold pooled
+ye2026_sepsis,C1Q-high monocyte (reference),real_lora__raw,-0.99664,0.22152,0.67728,1,5-fold pooled
+ye2026_sepsis,Cycling T/NK,real_lora__raw,-0.90067,0.33213,0.66062,0,5-fold pooled
+ye2026_sepsis,Cycling activated T (CD38/HLA-DR),real_lora__raw,-1.7519,0.16759,0.59191,0,5-fold pooled
+ye2026_sepsis,Proliferating T (label),real_lora__raw,-0.36674,0.38631,0.72278,0,5-fold pooled
+ye2026_sepsis,Plasmablast (label),real_lora__raw,-0.40104,0.19534,0.5925,1,5-fold pooled
+ye2026_sepsis,Plasmablast (markers),real_lora__raw,-1.5773,0.43119,0.69007,1,5-fold pooled
+ye2026_sepsis,MS1 monocyte (IL1R2+),real_lora__raw,-0.50546,0.58118,0.81559,1,5-fold pooled
+ye2026_sepsis,Cycling monocyte (Ye 2026),real_lora__raw,-2.1303,0.16176,0.57139,1,5-fold pooled
+ye2026_sepsis,ISG-high monocyte (positive control),real_lora__raw,-0.70608,0.65221,0.82927,1,5-fold pooled
+ye2026_sepsis,ISG-high T,real_lora__raw,-0.8138,0.69575,0.7906,1,5-fold pooled
+ye2026_sepsis,DN2 / ABC B,real_lora__raw,-1.7067,0.42306,0.74717,1,5-fold pooled
+ye2026_sepsis,HSPC,real_lora__raw,-1.3301,0.051877,0.55919,0,5-fold pooled
+ye2026_sepsis,Cytotoxic CD4 T,real_lora__raw,0.43312,0.69216,0.81202,1,5-fold pooled
+ye2026_sepsis,Granulocyte-like (LDG),real_lora__raw,-3.865,0.38264,0.65497,1,5-fold pooled
+imperial_eskd,C1Q-high monocyte (reference),zs__raw,-4.4053,0.1746,0.62114,0,5-fold pooled
+imperial_eskd,Cycling T/NK,zs__raw,1.7453,0.26355,0.63486,1,5-fold pooled
+imperial_eskd,Cycling activated T (CD38/HLA-DR),zs__raw,-0.56551,0.057545,0.52022,1,5-fold pooled
+imperial_eskd,Proliferating T (label),zs__raw,1.5611,0.5439,0.77844,1,5-fold pooled
+imperial_eskd,Plasmablast (label),zs__raw,-2.1527,0.30054,0.63133,1,5-fold pooled
+imperial_eskd,Plasmablast (markers),zs__raw,-2.2835,0.27004,0.60076,1,5-fold pooled
+imperial_eskd,MS1 monocyte (IL1R2+),zs__raw,-0.50379,0.46241,0.71926,1,5-fold pooled
+imperial_eskd,Cycling monocyte (Ye 2026),zs__raw,-3.061,0.052516,0.51907,1,5-fold pooled
+imperial_eskd,ISG-high monocyte (positive control),zs__raw,0.18981,0.81912,0.94839,1,5-fold pooled
+imperial_eskd,ISG-high T,zs__raw,-1.0172,0.77354,0.9082,1,5-fold pooled
+imperial_eskd,DN2 / ABC B,zs__raw,0.76768,0.19032,0.60897,1,5-fold pooled
+imperial_eskd,HSPC,zs__raw,-0.94186,0.13845,0.54586,1,5-fold pooled
+imperial_eskd,Cytotoxic CD4 T,zs__raw,0.0098678,0.15938,0.56291,0,5-fold pooled
+imperial_eskd,Granulocyte-like (LDG),zs__raw,-0.40858,0.2923,0.62648,0,5-fold pooled
+imperial_eskd,C1Q-high monocyte (reference),zs__cal,-2.6109,0.17248,0.65023,1,5-fold pooled
+imperial_eskd,Cycling T/NK,zs__cal,1.827,0.34712,0.69707,1,5-fold pooled
+imperial_eskd,Cycling activated T (CD38/HLA-DR),zs__cal,-0.33987,0.154,0.58194,1,5-fold pooled
+imperial_eskd,Proliferating T (label),zs__cal,0.75873,0.44134,0.72017,1,5-fold pooled
+imperial_eskd,Plasmablast (label),zs__cal,-1.3211,0.35945,0.65031,1,5-fold pooled
+imperial_eskd,Plasmablast (markers),zs__cal,-1.974,0.42007,0.67562,1,5-fold pooled
+imperial_eskd,MS1 monocyte (IL1R2+),zs__cal,1.3417,0.52802,0.74162,1,5-fold pooled
+imperial_eskd,Cycling monocyte (Ye 2026),zs__cal,-2.0301,0.32298,0.62582,1,5-fold pooled
+imperial_eskd,ISG-high monocyte (positive control),zs__cal,0.24206,0.86697,0.95891,1,5-fold pooled
+imperial_eskd,ISG-high T,zs__cal,-0.4629,0.79913,0.91075,1,5-fold pooled
+imperial_eskd,DN2 / ABC B,zs__cal,-1.0075,0.1315,0.58383,0,5-fold pooled
+imperial_eskd,HSPC,zs__cal,-0.0051408,0.16817,0.58859,1,5-fold pooled
+imperial_eskd,Cytotoxic CD4 T,zs__cal,1.9586,0.22763,0.62076,0,5-fold pooled
+imperial_eskd,Granulocyte-like (LDG),zs__cal,-3.4479,0.055175,0.5332,0,5-fold pooled
+imperial_eskd,C1Q-high monocyte (reference),scsemi__raw,-1.1436,0.16529,0.5538,1,5-fold pooled
+imperial_eskd,Cycling T/NK,scsemi__raw,-4.8187,0.053882,0.51274,1,5-fold pooled
+imperial_eskd,Cycling activated T (CD38/HLA-DR),scsemi__raw,-6.7839,0.10832,0.50616,0,5-fold pooled
+imperial_eskd,Proliferating T (label),scsemi__raw,-1.9643,0.29303,0.61637,1,5-fold pooled
+imperial_eskd,Plasmablast (label),scsemi__raw,-0.52439,0.13076,0.55539,1,5-fold pooled
+imperial_eskd,Plasmablast (markers),scsemi__raw,-1.2278,0.066058,0.52737,1,5-fold pooled
+imperial_eskd,MS1 monocyte (IL1R2+),scsemi__raw,-4.697,0.23486,0.51948,1,5-fold pooled
+imperial_eskd,Cycling monocyte (Ye 2026),scsemi__raw,,,0.5,0,5-fold pooled
+imperial_eskd,ISG-high monocyte (positive control),scsemi__raw,-0.25885,0.71148,0.80486,1,5-fold pooled
+imperial_eskd,ISG-high T,scsemi__raw,-0.8893,0.64154,0.75608,1,5-fold pooled
+imperial_eskd,DN2 / ABC B,scsemi__raw,-5.5176,0.086456,0.51257,1,5-fold pooled
+imperial_eskd,HSPC,scsemi__raw,-7.5597,-0.066676,0.5,0,5-fold pooled
+imperial_eskd,Cytotoxic CD4 T,scsemi__raw,1.8284,0.093167,0.57592,0,5-fold pooled
+imperial_eskd,Granulocyte-like (LDG),scsemi__raw,-9.6476,-0.027571,0.5,0,5-fold pooled
+imperial_eskd,C1Q-high monocyte (reference),real_lora__raw,-2.0746,0.070101,0.5563,1,5-fold pooled
+imperial_eskd,Cycling T/NK,real_lora__raw,-1.4198,0.23453,0.58909,1,5-fold pooled
+imperial_eskd,Cycling activated T (CD38/HLA-DR),real_lora__raw,-2.8306,0.13319,0.54915,1,5-fold pooled
+imperial_eskd,Proliferating T (label),real_lora__raw,0.5385,0.53938,0.77334,1,5-fold pooled
+imperial_eskd,Plasmablast (label),real_lora__raw,-0.037175,0.37215,0.66823,1,5-fold pooled
+imperial_eskd,Plasmablast (markers),real_lora__raw,-0.59279,0.41692,0.67102,1,5-fold pooled
+imperial_eskd,MS1 monocyte (IL1R2+),real_lora__raw,-0.91175,0.48684,0.67612,1,5-fold pooled
+imperial_eskd,Cycling monocyte (Ye 2026),real_lora__raw,-3.7049,0.11606,0.51709,1,5-fold pooled
+imperial_eskd,ISG-high monocyte (positive control),real_lora__raw,0.0162,0.79803,0.93664,1,5-fold pooled
+imperial_eskd,ISG-high T,real_lora__raw,-0.45676,0.74868,0.89785,1,5-fold pooled
+imperial_eskd,DN2 / ABC B,real_lora__raw,-2.1387,0.29104,0.64563,1,5-fold pooled
+imperial_eskd,HSPC,real_lora__raw,-0.49542,0.095651,0.55893,1,5-fold pooled
+imperial_eskd,Cytotoxic CD4 T,real_lora__raw,1.1634,0.35302,0.72508,0,5-fold pooled
+imperial_eskd,Granulocyte-like (LDG),real_lora__raw,-5.4426,0.031395,0.50197,0,5-fold pooled
+giroux2022,C1Q-high monocyte (reference),zs__raw,-3.7922,-0.62684,0.25694,0,5-fold pooled
+giroux2022,Cycling T/NK,zs__raw,-1.1571,0.18435,0.54167,1,5-fold pooled
+giroux2022,Cycling activated T (CD38/HLA-DR),zs__raw,-2.3242,0.24282,0.65972,1,5-fold pooled
+giroux2022,Proliferating T (label),zs__raw,-0.35243,0.46435,0.65972,1,5-fold pooled
+giroux2022,Plasmablast (label),zs__raw,-0.83162,0.22891,0.64931,0,5-fold pooled
+giroux2022,Plasmablast (markers),zs__raw,-1.7087,0.099106,0.56597,0,5-fold pooled
+giroux2022,MS1 monocyte (IL1R2+),zs__raw,0.11022,-0.078638,0.625,0,5-fold pooled
+giroux2022,Cycling monocyte (Ye 2026),zs__raw,-3.8804,0.24994,0.66667,1,5-fold pooled
+giroux2022,ISG-high monocyte (positive control),zs__raw,0.34126,0.78522,0.90278,1,5-fold pooled
+giroux2022,ISG-high T,zs__raw,-0.70336,0.58609,0.74306,1,5-fold pooled
+giroux2022,DN2 / ABC B,zs__raw,-0.57963,0.15355,0.61806,0,5-fold pooled
+giroux2022,HSPC,zs__raw,-0.65703,-0.31386,0.48611,1,5-fold pooled
+giroux2022,Cytotoxic CD4 T,zs__raw,-1.5039,0.46551,0.76389,1,5-fold pooled
+giroux2022,Granulocyte-like (LDG),zs__raw,-2.4718,0.46108,0.63542,1,5-fold pooled
+giroux2022,C1Q-high monocyte (reference),zs__cal,-2.6256,0.046928,0.66319,0,5-fold pooled
+giroux2022,Cycling T/NK,zs__cal,-3.0733,0.43788,0.60417,1,5-fold pooled
+giroux2022,Cycling activated T (CD38/HLA-DR),zs__cal,-4.1315,0.32333,0.625,0,5-fold pooled
+giroux2022,Proliferating T (label),zs__cal,-0.1136,0.27739,0.55556,1,5-fold pooled
+giroux2022,Plasmablast (label),zs__cal,-1.1046,0.46344,0.68403,0,5-fold pooled
+giroux2022,Plasmablast (markers),zs__cal,-2.9074,0.16126,0.62153,0,5-fold pooled
+giroux2022,MS1 monocyte (IL1R2+),zs__cal,2.0763,0.23105,0.63194,0,5-fold pooled
+giroux2022,Cycling monocyte (Ye 2026),zs__cal,-5.1532,0.10688,0.46875,1,5-fold pooled
+giroux2022,ISG-high monocyte (positive control),zs__cal,0.77333,0.7713,0.90278,1,5-fold pooled
+giroux2022,ISG-high T,zs__cal,-0.016223,0.81043,0.91667,1,5-fold pooled
+giroux2022,DN2 / ABC B,zs__cal,-2.1269,-0.028346,0.52083,0,5-fold pooled
+giroux2022,HSPC,zs__cal,-2.2367,-0.15229,0.54167,1,5-fold pooled
+giroux2022,Cytotoxic CD4 T,zs__cal,0.62402,0.38729,0.64583,1,5-fold pooled
+giroux2022,Granulocyte-like (LDG),zs__cal,-3.9365,0.35467,0.71528,1,5-fold pooled
+giroux2022,C1Q-high monocyte (reference),scsemi__raw,-3.5655,0.015918,0.45833,1,5-fold pooled
+giroux2022,Cycling T/NK,scsemi__raw,-2.6618,0.61554,0.71181,1,5-fold pooled
+giroux2022,Cycling activated T (CD38/HLA-DR),scsemi__raw,-1.7879,0.39802,0.56944,1,5-fold pooled
+giroux2022,Proliferating T (label),scsemi__raw,2.105,0.52261,0.625,1,5-fold pooled
+giroux2022,Plasmablast (label),scsemi__raw,-1.7354,-0.084437,0.54861,0,5-fold pooled
+giroux2022,Plasmablast (markers),scsemi__raw,0.42163,0.32824,0.62847,1,5-fold pooled
+giroux2022,MS1 monocyte (IL1R2+),scsemi__raw,,,,0,5-fold pooled
+giroux2022,Cycling monocyte (Ye 2026),scsemi__raw,-2.5057,-0.069628,0.51389,0,5-fold pooled
+giroux2022,ISG-high monocyte (positive control),scsemi__raw,1.0164,0.66854,0.70833,1,5-fold pooled
+giroux2022,ISG-high T,scsemi__raw,2.5134,0.71017,0.70833,1,5-fold pooled
+giroux2022,DN2 / ABC B,scsemi__raw,-3.6383,0.015094,0.54167,0,5-fold pooled
+giroux2022,HSPC,scsemi__raw,-2.814,-0.10244,0.49653,1,5-fold pooled
+giroux2022,Cytotoxic CD4 T,scsemi__raw,3.8103,0.62805,0.81944,1,5-fold pooled
+giroux2022,Granulocyte-like (LDG),scsemi__raw,,,0.5,0,5-fold pooled
+giroux2022,C1Q-high monocyte (reference),real_lora__raw,-2.887,0.16068,0.5625,1,5-fold pooled
+giroux2022,Cycling T/NK,real_lora__raw,-1.8241,0.36957,0.65972,1,5-fold pooled
+giroux2022,Cycling activated T (CD38/HLA-DR),real_lora__raw,-2.8981,0.58696,0.76389,1,5-fold pooled
+giroux2022,Proliferating T (label),real_lora__raw,-0.60792,0.5913,0.64583,1,5-fold pooled
+giroux2022,Plasmablast (label),real_lora__raw,-0.98916,0.24767,0.5,0,5-fold pooled
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+ji2025_chili,C1Q-high monocyte (reference),zs__raw,-4.7209,0.1654,0.53516,0,5-fold pooled
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+ji2025_chili,Cycling activated T (CD38/HLA-DR),zs__raw,-1.3286,0.3493,0.63672,1,5-fold pooled
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+ji2025_chili,ISG-high monocyte (positive control),zs__raw,3.2445,0.64357,0.83203,1,5-fold pooled
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+ji2025_chili,HSPC,zs__raw,-2.2118,0.048309,0.5332,0,5-fold pooled
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+ji2025_chili,Granulocyte-like (LDG),zs__raw,-0.92142,0.049946,0.5957,1,5-fold pooled
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+ji2025_chili,Cycling activated T (CD38/HLA-DR),zs__cal,-3.8155,0.34027,0.67188,1,5-fold pooled
+ji2025_chili,Proliferating T (label),zs__cal,-0.12541,0.18082,0.5625,1,5-fold pooled
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+ji2025_chili,Granulocyte-like (LDG),real_lora__raw,-5.8577,-0.030476,0.50781,1,5-fold pooled

paper-releases/pbisc-diffusion/updates/20261008T125804Z-deck-fig2-3-healthy-fig5-rare/diffusion/dataset/server_1/model8/presentations/2026-09-30--paper-summary--r00/data/fig5_rare_states_slide_text.json

@@ -0,0 +1,69 @@
+{
+ "section": "fig5-rare",
+ "scripts": [
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/tools/fig5_rare_states.py"
+ ],
+ "generated_from": "tools/fig5_rare_states.py (rerun to refresh; do not edit by hand)",
+ "slides": [
+  {
+   "title": "Rare states with 5 pairs: how many cells",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig5_rare_fraction.png"
+   ],
+   "keywords": [
+    "Within 2-fold: LoRA-5 19/56, scSemiProfiler-5 5/56",
+    "Closer to the observed fraction than scSemiProfiler-5: 51/56",
+    "Rare states kept, not averaged away"
+   ],
+   "footnote_short": "4 paired disease cohorts; 5 donors, mean of 5 draws. 0 = observed fraction; band = within 2-fold.",
+   "footnote": "Main comparison: 5 donors per draw (LoRA-5 vs scSemiProfiler with the same 5 donors as representatives, and zero-shot), every other usable sample tested, mean over 5 draws of log2(generated % / observed %) of the state within its parent type. Left: one point per state x cohort; below the diagonal = LoRA-5 closer; states a method never generates are drawn as 'not generated' (scSemiProfiler-5: 6 of 56; LoRA-5: 0). Zero-shot (no pairs) is closer than LoRA-5 on 28 of 56 fractions, LoRA-5 ranks donors better on 35 of 56. State × cohort pairs with ≥ 30 observed state cells in ≥ 3 donors (native depth); negative control left out. Marker rules from the literature (plans/rare_states_screen_20261004/tools/states.json); observed parent cells thinned to the generated depth; labels = the benchmark's frozen scANVI calls; the benchmark's Poisson read-out reproduced cell by cell. Source: data/fig5_rare_states.csv (plans/rare_states_paired_20261008/out/summary.csv).",
+   "numbers": [
+    {
+     "value": "{\"5 donors\": {\"n\": 56, \"frac_closer\": 51, \"within2_lora\": 19, \"within2_sc\": 5, \"not_generated_lora\": 0, \"not_generated_sc\": 6, \"rho_better\": 43, \"rho_median_lora\": 0.2381686657463106, \"rho_median_sc\": 0.17609850402537303, \"dir_lora\": 0.7321428571428571, \"dir_sc\": 0.6071428571428571}, \"5-fold\": {\"n\": 56, \"frac_closer\": 47, \"within2_lora\": 25, \"within2_sc\": 9, \"not_generated_lora\": 0, \"not_generated_sc\": 5, \"rho_better\": 38, \"rho_median_lora\": 0.31696815102004133, \"rho_median_sc\": 0.2431928042007824, \"dir_lora\": 0.8035714285714286, \"dir_sc\": 0.6785714285714286}}",
+     "source": "data/fig5_rare_states.csv"
+    }
+   ]
+  },
+  {
+   "title": "Rare states with 5 pairs: in the right donors",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig5_rare_donors.png"
+   ],
+   "keywords": [
+    "Donor ranking: median ρ 0.24 vs 0.18 (scSemiProfiler-5)",
+    "Better donor ranking than scSemiProfiler-5: 43/56",
+    "Disease direction kept: 73% vs 61% of draws"
+   ],
+   "footnote_short": "Spearman over donors of generated vs observed state %; direction = case-vs-control sign.",
+   "footnote": "Main comparison (5 donors, 5 draws). Left: Spearman over the tested donors of the generated vs observed (thinned) state percentage, mean over draws. Right: share of draws where the case-vs-control difference of donor means has the observed sign (sepsis vs controls, COVID+ vs COVID-, severe vs mild, ChILI vs controls). State × cohort pairs with ≥ 30 observed state cells in ≥ 3 donors (native depth); negative control left out. Marker rules from the literature (plans/rare_states_screen_20261004/tools/states.json); observed parent cells thinned to the generated depth; labels = the benchmark's frozen scANVI calls; the benchmark's Poisson read-out reproduced cell by cell. Source: data/fig5_rare_states.csv (out/summary.csv, out/contrasts.csv).",
+   "numbers": [
+    {
+     "value": "{\"5 donors\": {\"n\": 56, \"frac_closer\": 51, \"within2_lora\": 19, \"within2_sc\": 5, \"not_generated_lora\": 0, \"not_generated_sc\": 6, \"rho_better\": 43, \"rho_median_lora\": 0.2381686657463106, \"rho_median_sc\": 0.17609850402537303, \"dir_lora\": 0.7321428571428571, \"dir_sc\": 0.6071428571428571}, \"5-fold\": {\"n\": 56, \"frac_closer\": 47, \"within2_lora\": 25, \"within2_sc\": 9, \"not_generated_lora\": 0, \"not_generated_sc\": 5, \"rho_better\": 38, \"rho_median_lora\": 0.31696815102004133, \"rho_median_sc\": 0.2431928042007824, \"dir_lora\": 0.8035714285714286, \"dir_sc\": 0.6785714285714286}}",
+     "source": "data/fig5_rare_states.csv"
+    }
+   ]
+  },
+  {
+   "title": "5-fold CV: rare states",
+   "layout": "full",
+   "figures": [
+    "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/presentations/2026-09-30--paper-summary--r00/figures/fig5_rare_fivefold.png"
+   ],
+   "keywords": [
+    "Within 2-fold: LoRA 25/56, scSemiProfiler 9/56",
+    "Donor ranking: median ρ 0.32 vs 0.24",
+    "Better donor ranking: 38/56"
+   ],
+   "footnote_short": "Donor-level 5-fold CV, pooled; reported separately from the 5-pair comparison.",
+   "footnote": "Reported separately: 5-fold CV, every sample generated by the fold model that never trained on it; scSemiProfiler with exactly LoRA's training pairs as representatives. State × cohort pairs with ≥ 30 observed state cells in ≥ 3 donors (native depth); negative control left out. Marker rules from the literature (plans/rare_states_screen_20261004/tools/states.json); observed parent cells thinned to the generated depth; labels = the benchmark's frozen scANVI calls; the benchmark's Poisson read-out reproduced cell by cell. Source: data/fig5_rare_states.csv.",
+   "numbers": [
+    {
+     "value": "{\"5 donors\": {\"n\": 56, \"frac_closer\": 51, \"within2_lora\": 19, \"within2_sc\": 5, \"not_generated_lora\": 0, \"not_generated_sc\": 6, \"rho_better\": 43, \"rho_median_lora\": 0.2381686657463106, \"rho_median_sc\": 0.17609850402537303, \"dir_lora\": 0.7321428571428571, \"dir_sc\": 0.6071428571428571}, \"5-fold\": {\"n\": 56, \"frac_closer\": 47, \"within2_lora\": 25, \"within2_sc\": 9, \"not_generated_lora\": 0, \"not_generated_sc\": 5, \"rho_better\": 38, \"rho_median_lora\": 0.31696815102004133, \"rho_median_sc\": 0.2431928042007824, \"dir_lora\": 0.8035714285714286, \"dir_sc\": 0.6785714285714286}}",
+     "source": "data/fig5_rare_states.csv"
+    }
+   ]
+  }
+ ]
+}