{"id":"W6968615726","doi":"10.5281/zenodo.16796147","title":"Computational Tracking of Cell Origins Using CellSexID from Single-Cell Transcriptomes","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"In silico; Feature selection; Transplantation; Computational model; Tracking (education); Transcriptome; Feature (linguistics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059218,0.0005560358,0.0006118955,0.0004577344,0.0003587443,0.001009905,0.0008210916,0.0008164665,0.001787326],"category_scores_gemma":[0.001413112,0.000438483,0.0007904307,0.0003633141,0.000561801,0.0004969829,0.0008166248,0.0008894492,0.0004737245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008323336,"about_ca_system_score_gemma":0.0008514374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004223957,"about_ca_topic_score_gemma":0.006514964,"domain_scores_codex":[0.9998848,0.00002483025,0.000004332408,0.00005177004,0.0000221713,0.00001207819],"domain_scores_gemma":[0.9994941,0.0003425685,0.00004325727,0.00004905956,0.00003553007,0.0000355502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001106383,0.00003331668,0.003349904,0.00009546439,0.00005432631,0.00007927261,0.0000427302,0.963881,0.007542894,0.005372325,0.001205921,0.01823218],"study_design_scores_gemma":[0.000003105988,0.000005245037,0.0001622118,0.000002447048,0.00000317476,0.000008878963,0.000003846504,0.9960347,0.001149246,0.002260253,0.0003640271,0.000002951186],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1379644,0.0004480428,0.8527587,0.0003616514,0.00007433822,0.00005176436,0.002230818,0.003142495,0.002967643],"genre_scores_gemma":[0.6684947,0.0004828107,0.3178683,0.0003161591,0.00004982937,0.000325544,0.007334834,0.0005873578,0.004540514],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004223957,"threshold_uncertainty_score":0.008398712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03139402785246861,"score_gpt":0.2378902015184833,"score_spread":0.2064961736660147,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}