Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261001T023742Z-deck-calibration-giroux-sexgenes/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/data/sex_linked_genes/README.md

@@ -0,0 +1,57 @@
+# Sex-chromosome-linked genes excluded from the disease-signal scores
+
+**Why.** In Giroux 2022 the scored contrast (GEO "severe" = paper "moderate" vs mild) is almost fully confounded with
+sex. Sex was called from bulk chrY CPM (RPS4Y1, DDX3Y, KDM5D, UTY, EIF1AY): females ≤ 3 CPM, males ≥ 780 CPM, giving
+severe 4 F / 1 M and mild 0 F / 5 M subjects. The observed top-DEG lists and the bulk-broadcast list were led by chrY
+genes and X genes that escape X inactivation. User decision 2026-10-01: rescore Giroux's disease-signal metrics
+(logFC r, partial r, top-50 DEG overlap and the broadcast baseline) without sex-linked genes. The other paired cohorts
+are sex-balanced between case and control and keep their original scores (sensitivity run in `scores_nosex/`).
+
+**Built by** `tools/build_sex_gene_list.py` (CPU, no network; rerun to rebuild). Nothing is typed in by hand.
+
+## Definition (on the 20,097 protein-coding gene axis of `data/<cohort>/features.npz`)
+
+1. **chrY non-PAR**: every axis gene that GENCODE v50 places on chrY and that does not lie entirely inside a chrY
+   pseudo-autosomal region. 61 axis genes are on chrY; 18 are PAR copies (kept), **43 are excluded**.
+2. **chrX XCI escape**: every gene of Tukiainen et al. 2017, Supplementary Table 13, whose *Reported XCI status* is
+   **Escape** or **Variable** (variable escape), plus the genes the paper flags in the column *Possible new call for
+   escape*. 178 table rows are selected (82 Escape, 89 Variable, 7 new calls); 10 are not on the protein-coding axis
+   (XIST, JPX, LINC00106, five clone-named lncRNAs, GLRA4, CXorf30), 15 lie in a PAR and are kept, **153 are excluded** (62 Escape, 85 Variable,
+   6 new calls). Mapping is by Ensembl gene id with the version stripped; one retired id (IKBKG,
+   ENSG00000073009 → ENSG00000269335) is mapped by its unique chrX symbol in GENCODE v50.
+
+**Total: 196 genes** (`sex_linked_genes_exclude.csv`). The scorer drops only those that are scoring genes of the
+cohort (Giroux: 65 of 196; the contrast and DEG then use 5,498 of 5,563 scoring genes).
+
+### How PAR genes were identified
+GENCODE v50 (Ensembl 116) gives the chrY PAR copies their own gene ids (ENSG00000292xxx) and carries no `PAR` tag or
+`_PAR_Y` suffix, so PAR status is assigned by coordinates: a gene is PAR when its GENCODE v50 interval lies entirely
+inside PAR1 or PAR2 of its chromosome, with the PAR intervals read from the GRC region report of GRCh38.p14
+(PAR#1 X/Y 10,001–2,781,479; PAR#2 X 155,701,383–156,030,895, Y 56,887,903–57,217,415). For every selected Tukiainen gene on the
+axis the coordinate call agrees with Tukiainen's own *Region* column. Three chrX genes cross a PAR boundary (XG, TMLHE, SPRY3) and count as non-PAR; of
+these only XG is an escape gene, and it is excluded (`par_genes_on_axis.csv` lists all PAR / boundary genes).
+
+## Files
+| file | content |
+|---|---|
+| `sex_linked_genes_exclude.csv` | the full list: `gene_id`, `symbol`, `chromosome`, `reason`, GENCODE v50 `start`/`end`, Tukiainen status / region / mapping |
+| `chrY_nonPAR_genes.csv` | the 43 chrY non-PAR genes only (chrY-only sensitivity run) |
+| `tukiainen2017_mapping.csv` | every selected Tukiainen row and what happened to it (excluded / PAR kept / not on the axis) |
+| `par_genes_on_axis.csv` | axis genes inside a PAR or crossing a PAR boundary |
+| `BUILD.json` | input sha256s, counts, PAR intervals |
+| `sources/` | the downloaded source files (below) |
+
+## Sources
+- **Tukiainen T, Villani A-C, Yen A, Rivas MA, Marshall JL, Satija R, et al. Landscape of X chromosome inactivation
+  across human tissues. *Nature* 550, 244–248 (2017). doi:10.1038/nature24265 (PMC5685192).**
+  Supplementary Tables ZIP downloaded 2026-10-01 from
+  `https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fnature24265/MediaObjects/41586_2017_BFnature24265_MOESM3_ESM.zip`
+  → `sources/41586_2017_BFnature24265_MOESM3_ESM.zip` (sha256 4578fd68…). `sources/Tukiainen2017_Suppl.Table.13.xlsx` is
+  `nature24265-s3/Suppl.Table.13.xlsx` from that ZIP, byte-identical (sha256 eb7d466f…). Its footnote: *Reported XCI
+  status refers to the genic XCI status in the combined list from Carrel & Willard (Nature, 2005) and Cotton et al
+  (Genome Biol., 2013).*
+- **PAR intervals**: Genome Reference Consortium, GRCh38.p14 assembly regions report,
+  `https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/001/405/GCF_000001405.40_GRCh38.p14/GCF_000001405.40_GRCh38.p14_assembly_regions.txt`
+  → `sources/GCF_000001405.40_GRCh38.p14_assembly_regions.txt` (sha256 8e6faeaa…).
+- **Gene coordinates**: GENCODE v50 comprehensive annotation GTF, `/home/sj_server_1/gblee/ablations_data_repro_20260802/fixed_assets/gencode.v50.annotation.gtf.gz`
+  (all 20,097 axis genes are present in it).

paper-releases/pbisc-diffusion/updates/20261001T023742Z-deck-calibration-giroux-sexgenes/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores_nosex/ye2026_sepsis/pooled_deg/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
+pseudo_full__cal,T cell,mean_cp10k,3231,0.24777112571149595,0.19551309101666997,0.16472305315231422,0.6171498105296672,61,21,61,21,298117,61266,,,,,,,,,,,
+pseudo_full__cal,T cell,pseudobulk_log1p_cpm,3231,0.20408015272760524,0.2010999345675154,0.11618528236235502,0.537621790474339,61,21,61,21,298117,61266,,,,,,,,,,,
+pseudo_full__cal,B cell,mean_cp10k,3285,0.31627341293652894,0.25036708089906523,0.2345513402195853,0.4560628954234591,61,21,61,21,99729,20840,,,,,,,,,,,
+pseudo_full__cal,B cell,pseudobulk_log1p_cpm,3285,0.27596278677478203,0.26082494445502535,0.19921831201459703,0.37426613473009473,61,21,61,21,99729,20840,,,,,,,,,,,
+pseudo_full__cal,Monocyte,mean_cp10k,3263,0.5158430651737392,0.5435876122268675,0.31045592644080183,0.5479622113848005,61,21,61,21,111269,26421,,,,,,,,,,,
+pseudo_full__cal,Monocyte,pseudobulk_log1p_cpm,3263,0.40064330089472733,0.6083776941543844,0.07926530607408054,0.5738606438906191,61,21,61,21,111269,26421,,,,,,,,,,,
+pseudo_full__cal,NK cell,mean_cp10k,3212,0.09851903345279528,0.11749959620699715,0.048505176851464285,0.47848598318489566,61,21,61,21,47832,8260,,,,,,,,,,,
+pseudo_full__cal,NK cell,pseudobulk_log1p_cpm,3212,0.06693908134759274,0.03883253056271272,0.05933230968368416,0.242678515897229,61,21,61,21,47832,8260,,,,,,,,,,,
+pseudo_full__cal,T cell,welch_top50_deg,5908,,,,,61,21,61,21,298117,61266,True,1,0.012195121951219513,50,33,1585,33,3,0.030927835051546393,50,934
+pseudo_full__cal,B cell,welch_top50_deg,5908,,,,,61,21,61,21,99729,20840,True,1,0.010101010101010102,50,50,1094,147,3,0.030927835051546393,50,934
+pseudo_full__cal,Monocyte,welch_top50_deg,5908,,,,,61,21,61,21,111269,26421,True,9,0.0989010989010989,50,50,2447,279,12,0.13636363636363635,50,934
+pseudo_full__cal,NK cell,welch_top50_deg,5908,,,,,61,21,61,21,47832,8260,True,0,0.0,50,19,1234,19,2,0.02040816326530612,50,934
+pseudo_full__cal,DC,welch_top50_deg,5908,,,,,57,21,56,20,3300,823,True,4,0.041666666666666664,50,50,1566,113,1,0.010101010101010102,50,934
+pseudo_full__raw,T cell,mean_cp10k,3231,0.00997163975553426,0.2538097966219658,-0.10531717595037624,0.40606593513675726,61,21,61,21,298117,44589,,,,,,,,,,,
+pseudo_full__raw,T cell,pseudobulk_log1p_cpm,3231,0.07503629624959823,0.21433104605137301,0.005545240410352077,0.3262066154426082,61,21,61,21,298117,44589,,,,,,,,,,,
+pseudo_full__raw,B cell,mean_cp10k,3285,0.21814015864049927,0.27512676730624724,0.1453969394936253,0.30978835915450004,61,21,61,21,99729,23039,,,,,,,,,,,
+pseudo_full__raw,B cell,pseudobulk_log1p_cpm,3285,0.1812778273588157,0.2704489845153215,0.10900677131032244,0.30013647266993737,61,21,61,21,99729,23039,,,,,,,,,,,
+pseudo_full__raw,Monocyte,mean_cp10k,3263,0.33544711795748045,0.5454915657329948,0.1505589406832077,0.40326266381226805,61,21,61,21,111269,37691,,,,,,,,,,,
+pseudo_full__raw,Monocyte,pseudobulk_log1p_cpm,3263,0.371465327014345,0.616079535832396,0.08810503318029535,0.5057743915583107,61,21,61,21,111269,37691,,,,,,,,,,,
+pseudo_full__raw,NK cell,mean_cp10k,3212,0.02791682736947,0.18603492677118083,-0.043243919272455585,0.36288623258292063,61,21,61,21,47832,10755,,,,,,,,,,,
+pseudo_full__raw,NK cell,pseudobulk_log1p_cpm,3212,0.11331081743761953,0.05318529242438908,0.1047329421919489,0.2064196920184666,61,21,61,21,47832,10755,,,,,,,,,,,
+pseudo_full__raw,T cell,welch_top50_deg,5908,,,,,61,21,61,21,298117,44589,True,1,0.010101010101010102,50,50,1585,62,3,0.030927835051546393,50,1376
+pseudo_full__raw,B cell,welch_top50_deg,5908,,,,,61,21,61,21,99729,23039,True,0,0.0,50,50,1094,130,2,0.02040816326530612,50,1376
+pseudo_full__raw,Monocyte,welch_top50_deg,5908,,,,,61,21,61,21,111269,37691,True,5,0.05263157894736842,50,50,2447,640,12,0.13636363636363635,50,1376
+pseudo_full__raw,NK cell,welch_top50_deg,5908,,,,,61,21,61,21,47832,10755,True,3,0.0379746835443038,50,32,1234,32,2,0.02040816326530612,50,1376
+pseudo_full__raw,DC,welch_top50_deg,5908,,,,,57,21,57,21,3300,717,True,1,0.018518518518518517,50,5,1566,5,1,0.010101010101010102,50,1376
+real_lora__raw,T cell,mean_cp10k,3231,0.6266015859808247,0.2538097966219658,0.5938549893619387,0.3426017340285674,61,21,61,21,298117,67850,,,,,,,,,,,
+real_lora__raw,T cell,pseudobulk_log1p_cpm,3231,0.61040477757534,0.21433104605137301,0.5863812860708123,0.29269564646306395,61,21,61,21,298117,67850,,,,,,,,,,,
+real_lora__raw,B cell,mean_cp10k,3285,0.5659323920528541,0.27512676730624724,0.5372946184623114,0.22962484007901524,61,21,61,21,99729,19896,,,,,,,,,,,
+real_lora__raw,B cell,pseudobulk_log1p_cpm,3285,0.44629076107583887,0.2704489845153215,0.42283966936272793,0.16581151615505665,61,21,61,21,99729,19896,,,,,,,,,,,
+real_lora__raw,Monocyte,mean_cp10k,3263,0.5738039044241521,0.5454915657329948,0.43148236959329667,0.46498112716477047,61,21,61,21,111269,22723,,,,,,,,,,,
+real_lora__raw,Monocyte,pseudobulk_log1p_cpm,3263,0.5769217389087976,0.616079535832396,0.3822948369074442,0.5184933213004457,61,21,61,21,111269,22723,,,,,,,,,,,
+real_lora__raw,NK cell,mean_cp10k,3212,0.3376909719566291,0.18603492677118083,0.3103149840390365,0.21437766017042395,61,21,61,21,47832,7728,,,,,,,,,,,
+real_lora__raw,NK cell,pseudobulk_log1p_cpm,3212,0.34505564330719096,0.05318529242438908,0.34344372022507863,0.04638928649133336,61,21,61,21,47832,7728,,,,,,,,,,,
+real_lora__raw,T cell,welch_top50_deg,5908,,,,,61,21,61,21,298117,67850,True,1,0.016129032258064516,50,13,1585,13,3,0.030927835051546393,50,1376
+real_lora__raw,B cell,welch_top50_deg,5908,,,,,61,21,61,21,99729,19896,True,1,0.010101010101010102,50,50,1094,53,2,0.02040816326530612,50,1376
+real_lora__raw,Monocyte,welch_top50_deg,5908,,,,,61,21,61,21,111269,22723,True,19,0.2345679012345679,50,50,2447,499,12,0.13636363636363635,50,1376
+real_lora__raw,NK cell,welch_top50_deg,5908,,,,,61,21,61,21,47832,7728,True,0,0.0,50,13,1234,13,2,0.02040816326530612,50,1376
+real_lora__raw,DC,welch_top50_deg,5908,,,,,57,21,53,21,3300,683,True,2,0.02247191011235955,50,41,1566,41,1,0.010101010101010102,50,1376
+zs__cal,T cell,mean_cp10k,3231,0.041542620869238815,0.19551309101666997,-0.036704881579049796,0.3825857512256667,61,21,61,21,298117,60913,,,,,,,,,,,
+zs__cal,T cell,pseudobulk_log1p_cpm,3231,0.07296924802966989,0.2010999345675154,-0.023761972574600432,0.46530347973477276,61,21,61,21,298117,60913,,,,,,,,,,,
+zs__cal,B cell,mean_cp10k,3285,0.16090065212288904,0.25036708089906523,0.08817114145665349,0.3195883836408943,61,21,61,21,99729,19241,,,,,,,,,,,
+zs__cal,B cell,pseudobulk_log1p_cpm,3285,0.1710123036679853,0.26082494445502535,0.104525687789726,0.2848026182787119,61,21,61,21,99729,19241,,,,,,,,,,,
+zs__cal,Monocyte,mean_cp10k,3263,0.24319666135501508,0.5435876122268675,0.0986971436588896,0.3021151374294907,61,21,61,21,111269,30651,,,,,,,,,,,
+zs__cal,Monocyte,pseudobulk_log1p_cpm,3263,0.14645133495589396,0.6083776941543844,-0.10169469865825387,0.36427321254806894,61,21,61,21,111269,30651,,,,,,,,,,,
+zs__cal,NK cell,mean_cp10k,3212,0.04056255655587307,0.11749959620699715,0.006464229321030083,0.29297799539241204,61,21,61,21,47832,7424,,,,,,,,,,,
+zs__cal,NK cell,pseudobulk_log1p_cpm,3212,-0.0400531636251055,0.03883253056271272,-0.0502163420099494,0.22700784572146643,61,21,61,21,47832,7424,,,,,,,,,,,
+zs__cal,T cell,welch_top50_deg,5908,,,,,61,21,61,21,298117,60913,True,5,0.05263157894736842,50,50,1585,261,3,0.030927835051546393,50,934
+zs__cal,B cell,welch_top50_deg,5908,,,,,61,21,61,21,99729,19241,True,1,0.010101010101010102,50,50,1094,346,3,0.030927835051546393,50,934
+zs__cal,Monocyte,welch_top50_deg,5908,,,,,61,21,61,21,111269,30651,True,4,0.041666666666666664,50,50,2447,526,12,0.13636363636363635,50,934
+zs__cal,NK cell,welch_top50_deg,5908,,,,,61,21,61,21,47832,7424,True,0,0.0,50,50,1234,70,2,0.02040816326530612,50,934
+zs__cal,DC,welch_top50_deg,5908,,,,,57,21,59,21,3300,1531,True,0,0.0,50,20,1566,20,1,0.010101010101010102,50,934
+zs__raw,T cell,mean_cp10k,3231,-0.11028938292820233,0.2538097966219658,-0.1797512843669882,0.23182437597853697,61,21,61,21,298117,43347,,,,,,,,,,,
+zs__raw,T cell,pseudobulk_log1p_cpm,3231,-0.03229415534934764,0.21433104605137301,-0.09766345157655273,0.2769885607443443,61,21,61,21,298117,43347,,,,,,,,,,,
+zs__raw,B cell,mean_cp10k,3285,0.06208367144277927,0.27512676730624724,0.0053579156568959755,0.2073388488185968,61,21,61,21,99729,18316,,,,,,,,,,,
+zs__raw,B cell,pseudobulk_log1p_cpm,3285,0.09435028191199768,0.2704489845153215,0.03962304566574639,0.21099202156378186,61,21,61,21,99729,18316,,,,,,,,,,,
+zs__raw,Monocyte,mean_cp10k,3263,0.06776281323630755,0.5454915657329948,-0.07675312602564967,0.23874011287108995,61,21,61,21,111269,45474,,,,,,,,,,,
+zs__raw,Monocyte,pseudobulk_log1p_cpm,3263,0.1901937382776148,0.616079535832396,-0.059620352370181026,0.37924880008050305,61,21,61,21,111269,45474,,,,,,,,,,,
+zs__raw,NK cell,mean_cp10k,3212,-0.07104490208142046,0.18603492677118083,-0.13046479301089486,0.27966478436692144,61,21,61,21,47832,11566,,,,,,,,,,,
+zs__raw,NK cell,pseudobulk_log1p_cpm,3212,-0.02477507019062832,0.05318529242438908,-0.0399699773410567,0.2590218036049151,61,21,61,21,47832,11566,,,,,,,,,,,
+zs__raw,T cell,welch_top50_deg,5908,,,,,61,21,61,21,298117,43347,True,3,0.030927835051546393,50,50,1585,709,3,0.030927835051546393,50,1376
+zs__raw,B cell,welch_top50_deg,5908,,,,,61,21,61,21,99729,18316,True,0,0.0,50,50,1094,537,2,0.02040816326530612,50,1376
+zs__raw,Monocyte,welch_top50_deg,5908,,,,,61,21,61,21,111269,45474,True,4,0.041666666666666664,50,50,2447,969,12,0.13636363636363635,50,1376
+zs__raw,NK cell,welch_top50_deg,5908,,,,,61,21,61,21,47832,11566,True,1,0.010101010101010102,50,50,1234,409,2,0.02040816326530612,50,1376
+zs__raw,DC,welch_top50_deg,5908,,,,,57,21,57,21,3300,1191,True,1,0.011904761904761904,50,35,1566,35,1,0.010101010101010102,50,1376

paper-releases/pbisc-diffusion/updates/20261001T023742Z-deck-calibration-giroux-sexgenes/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores_nosex/ye2026_sepsis/pooled_deg/summary.json

@@ -0,0 +1,2209 @@
+{
+ "schema": "paired_ft_scores.v1",
+ "dataset": "ye2026_sepsis",
+ "written_utc": "2026-10-01T01:56:59.751661+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",
+  "--threads",
+  "6",
+  "--arm",
+  "pseudo_full__cal=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/pseudo_full__cal.npz",
+  "--arm",
+  "pseudo_full__raw=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/pseudo_full__raw.npz",
+  "--arm",
+  "real_lora__raw=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/real_lora__raw.npz",
+  "--arm",
+  "zs__cal=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/zs__cal.npz",
+  "--arm",
+  "zs__raw=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/zs__raw.npz",
+  "--case-groups",
+  "adult_sepsis,ped_sepsis",
+  "--control-groups",
+  "adult_HC,adult_ICU_ctrl,ped_HC,ped_ICU_ctrl",
+  "--condition",
+  "pseudo_full__cal=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/conditions_pooled_cal.npz",
+  "--condition",
+  "pseudo_full__raw=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/conditions_pooled_raw.npz",
+  "--condition",
+  "real_lora__raw=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/conditions_pooled_raw.npz",
+  "--condition",
+  "zs__cal=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/conditions_pooled_cal.npz",
+  "--condition",
+  "zs__raw=/tmp/claude-1000/-home-sj-server-1/c8102cb0-e04f-4e04-adda-0728604e4435/scratchpad/gen/ye2026_sepsis/pooled/conditions_pooled_raw.npz",
+  "--out",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scores_nosex/ye2026_sepsis/pooled_deg",
+  "--exclude-genes",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/sex_linked_genes/sex_linked_genes_exclude.csv",
+  "--reuse-labels",
+  "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scores/ye2026_sepsis/pooled_deg"
+ ],
+ "arms": [
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+  "pseudo_full__raw",
+  "real_lora__raw",
+  "zs__cal",
+  "zs__raw"
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+  "score": "top-50 DEG overlap per cell type (benchmark total_top50_overlap, Welch backend)",
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+   "top_deg_genes",
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+  "broadcast": "welch_bh_deg + top_deg_genes on the arm's condition bulk_counts (scoring genes, case|control donors), one list compared with every type's observed list (sle_broadcast.py broadcast_input_bulk); not part of the published benchmark"
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