{"id":"W2949679909","doi":"10.1093/bioinformatics/btz112","title":"SUBSTRA: Supervised Bayesian Patient Stratification","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Simon Fraser University","funders":"","keywords":"Computer science; Benchmark (surveying); Machine learning; Bayesian probability; Artificial intelligence; Population stratification; Source code; Data mining; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001752646,0.0001124502,0.0001151965,0.00008431879,0.0000756025,0.0001505901,0.0005450009,0.00006855594,0.00007194986],"category_scores_gemma":[0.00003335801,0.0001007191,0.00004041505,0.0002544329,0.00001265059,0.0006184375,0.00009049875,0.0001637668,0.0007824961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004610397,"about_ca_system_score_gemma":0.00009452539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002471633,"about_ca_topic_score_gemma":0.000005060583,"domain_scores_codex":[0.9988644,0.00003744328,0.0003985402,0.0001417867,0.0003194853,0.0002383819],"domain_scores_gemma":[0.9988744,0.00005568299,0.0001486683,0.0007358362,0.00008598763,0.00009937614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001051493,0.0001171238,0.05716277,0.0008837566,0.00002685215,0.000005047166,0.02444259,0.002804348,0.00024513,0.2249444,0.002572861,0.6867846],"study_design_scores_gemma":[0.0001631122,0.0001419635,0.01152084,0.00002422687,0.000001461096,0.000009153016,0.0002634807,0.9836274,0.0003003678,0.000455033,0.003324409,0.0001685361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3267312,0.00007700677,0.6211884,0.002876322,0.001480846,0.001188693,0.000009562161,0.000700932,0.04574705],"genre_scores_gemma":[0.8504633,0.00000410695,0.1489629,0.0004207878,0.00001913423,0.000007616184,0.00001835025,0.000006234276,0.000097568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9808231,"threshold_uncertainty_score":0.9999955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343383508080151,"score_gpt":0.2444275040129084,"score_spread":0.2309936689321069,"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."}}