{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006525278,0.0009339827,0.001291996,0.001014676,0.000607817,0.0009065972,0.001613545,0.001028848,0.004276438],"category_scores_gemma":[0.0166846,0.0005680759,0.001113018,0.0008162355,0.0009989304,0.0008368682,0.001825793,0.001828693,0.002575882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00069806,"about_ca_system_score_gemma":0.00258995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003134271,"about_ca_topic_score_gemma":0.005327513,"domain_scores_codex":[0.9963272,0.002402385,0.0001629422,0.0006408969,0.0003632199,0.0001033097],"domain_scores_gemma":[0.993196,0.00441609,0.000545215,0.0008081485,0.0007225836,0.0003119053],"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":[0.00212084,0.0005359141,0.04965516,0.000831633,0.000734556,0.0003188078,0.0004734583,0.1896176,0.006049939,0.02623125,0.05563351,0.6677974],"study_design_scores_gemma":[0.0003634304,0.0002872823,0.005408458,0.0001271786,0.0001289868,0.0004246214,0.00005401561,0.9109127,0.003326818,0.06845812,0.01044563,0.00006275991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03253236,0.00108607,0.9538382,0.002252953,0.0001590143,0.0006178339,0.003682344,0.003530435,0.002300791],"genre_scores_gemma":[0.4466196,0.0006878274,0.5349054,0.001955995,0.0006315426,0.001201601,0.009812184,0.0005415323,0.003644344],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006525278,"threshold_uncertainty_score":0.03450936,"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."}}