Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261012T130738Z-strictpairs-implementation/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/archive/20261012T130738Z-strictpairs-implementation/snapshot/scsemi/immicro/healthy/fold0/n5/geneset_feature_qc.json

@@ -0,0 +1,36 @@
+{
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+ "selected_gene_sets": 727,
+ "reps": {
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+   "median_nonzero_genes": 147.0,
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+  "HS30": {
+   "n_cells": 6447,
+   "median_thresholded_gene_library": 8900.81640625,
+   "median_nonzero_genes": 140.0,
+   "zero_score_pathways": 157
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+  "HS53": {
+   "n_cells": 1544,
+   "median_thresholded_gene_library": 8720.443359375,
+   "median_nonzero_genes": 135.0,
+   "zero_score_pathways": 208
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+  "HS39": {
+   "n_cells": 2056,
+   "median_thresholded_gene_library": 8802.19140625,
+   "median_nonzero_genes": 140.0,
+   "zero_score_pathways": 198
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+  "HS109": {
+   "n_cells": 4265,
+   "median_thresholded_gene_library": 8649.681640625,
+   "median_nonzero_genes": 148.0,
+   "zero_score_pathways": 143
+  }
+ }
+}

paper-releases/pbisc-diffusion/updates/20261012T130738Z-strictpairs-implementation/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/archive/20261012T130738Z-strictpairs-implementation/snapshot/scsemi/immicro/healthy/fold0/n5/prepared.json

@@ -0,0 +1,24 @@
+{
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+ "seconds": 24.7,
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+  "hvset.npy": "fe1a973eed15cb195e77f923e9847c92a850e6fc685b3e31367112c4def1ae0e",
+  "hvmask.npy": "3e426aa09b0c4573cb9c197d96c9525c86671bb5fe57b5df31d42f0704393751",
+  "status/init_representatives.txt": "a6f5276de80cdf6650a9432b26b1aa86061f0a780e5c30cee0a5ad297804606c",
+  "status/init_cluster_labels.txt": "9d040d2e601812ef872f0ad09ad5c4e5819550a6e0e6b37772966d979d5e55e5",
+  "sample_sc/HS40.h5ad": "c2d6f8f9ba475f2d741eaee91e06741b07bff3eac0e8c0543c291f2e3e018415",
+  "sample_sc/HS30.h5ad": "200b8d9d202371b64278056e8b51108267e3cc47a6ee94c5c5e523cf391a763a",
+  "sample_sc/HS53.h5ad": "303bb684d1339009d9059c79bffd23f3b1cbfbdaa961934a3f15a485f01acf6f",
+  "sample_sc/HS39.h5ad": "a32bc4cfb15e18aa3d8e9299ff5b11b2fb906f7262e5984dc141b873dec47f28",
+  "sample_sc/HS109.h5ad": "9ad6b70a37439ac1956e5d8dc481d746a0311e4c23d81f07f49231e1141e3fe3",
+  "geneset_scores/HS40.npy": "a2f33022e7c3f4468dfe00ab3ccc7170252a000a814ad94d836ca7cab73e73db",
+  "geneset_scores/HS30.npy": "060e98fc0e69ca9148eee28e7ad266ba30eda1e70fc996ecf640944b0c47ff02",
+  "geneset_scores/HS53.npy": "edfdf5d3e97531cf123422e0197093a037159e1203e194a7c0317e0d9e7dbc4e",
+  "geneset_scores/HS39.npy": "428f3b7c8756bd70eea495560f5c7907145e7839e1386bac47dd46f7fe43ecbe",
+  "geneset_scores/HS109.npy": "a2a8a07578b2f90afd6ead5d330ba9343f6204896ebae4c9ab83f3e54e12a605"
+ },
+ "genesets_gmt_sha256": "9c4386ac1ff666fc88301e126f1a1c6452122c6b63f311131a640bffe9c4d84b"
+}

paper-releases/pbisc-diffusion/updates/20261012T130738Z-strictpairs-implementation/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/archive/20261012T130738Z-strictpairs-implementation/snapshot/scsemi/immicro/healthy/fold0/n5/run_manifest.json

@@ -0,0 +1,103 @@
+{
+ "run_signature": "8927b9166cd6e332a8e35708cc1fe9711f00c9e4fbd5f4f4d58e4936ae1f319f",
+ "protocol": {
+  "method": "scSemiProfiler",
+  "setting": "paired_fixed_representatives_realbulk_genesets",
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+   "cellfilter": false,
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+   "geneset": true,
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+  "representatives": "fixed: every usable row of the split's training donors (no active learning)",
+  "assignment": "upstream representative_selection.update_membership: nearest representative by Euclidean distance in processed_bulkdata.obsm['X_pca'] (initsetup PCA of log1p CP10K real bulk)",
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+   "ministages": 5,
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+  "seeds": {
+   "base": 20260927,
+   "pretrain1": "base + 1000 + bulk row index",
+   "pretrain2": "base + 2000 + bulk row index",
+   "target": "base + bulk row index (frozen campaign rule)"
+  },
+  "output_unit": "normalized_expression (upstream fast_semi output: ZINB mean, rep-cell library, values <= 10 zeroed)",
+  "cellgraph_impl": "tools/lean_cellgraph.fast_cellgraph_lean replaces upstream singlecell_process.fast_cellgraph inside scprocess: same arithmetic, chunked (16 GiB CPU cap); bit-identical outputs verified (validation/lean_cellgraph_*.json)",
+  "scprocess_orchestration": "cohort hvset first (upstream scprocess's own steps: sorted sample_ids, normalize_total 1e4, dense, X*(X>10), getGeneSetMatrix score formula, concatenate, log1p, highly_variable_genes) -> hvset.npy; then upstream scprocess once per representative (it skips hvset when hvset.npy exists). Bit-identical to one scprocess call over all representatives (validation/prepared_*.json); peak memory is one representative",
+  "hvset_impl": "tools/lean_hvset.cohort_hvset_lean: streamed, one representative in memory; output-identical to cohort_hvset (validation/hvset_dependence_20261002.json)"
+ },
+ "inputs": {
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+  "rep_sc.h5ad": "ab00c585b03386a898ea9564e25d1e41ea10f818830065317e05297f41d29b87"
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+  "commit": "c2aea021188759e56ecf14578915c0237aaa75d2",
+  "compatibility_patch_sha256": "314d353002ffb482b4ed4b61a32b280a50ff8b6a9933512ada9fdc74c17b1711",
+  "changes": [
+   "remove unused scvi.nn.one_hot import",
+   "translate legacy use_gpu to accelerator/devices",
+   "avoid empty slice when geneset_len is zero",
+   "drop a size-1 trailing training batch: scvi DataSplitter(drop_last=True) only when n_obs % batch_size == 1 (upstream's own commented-out remedy); all other cell counts unchanged"
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+}