{"id":"W3104089851","doi":"10.1161/circ.142.suppl_3.16998","title":"Abstract 16998: Gender and Age Specific Baseline Predictors of MACE in PEACE Trial Identified by Machine Learning","year":2020,"lang":"en","type":"article","venue":"Circulation","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mace; Medicine; Internal medicine; Myocardial infarction; Proportional hazards model; Clinical endpoint; Ejection fraction; Cardiology; Randomized controlled trial; Demography; Percutaneous coronary intervention; Heart failure","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00182273,0.0005214086,0.0008594008,0.0002162119,0.0002358793,0.0007017771,0.0003457646,0.0004843428,0.005534154],"category_scores_gemma":[0.001949868,0.0001653559,0.001072284,0.0002472317,0.0002220466,0.0004999471,0.0003617985,0.001403973,0.0008765057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001603986,"about_ca_system_score_gemma":0.0003809903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004694859,"about_ca_topic_score_gemma":0.0008512625,"domain_scores_codex":[0.9996437,0.0001853614,0.00002108842,0.00006957809,0.00003731492,0.00004296798],"domain_scores_gemma":[0.9995777,0.0001443039,0.00009131721,0.00004744048,0.00004245519,0.00009686168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.5777528,0.005738812,0.2135922,0.002734003,0.008681752,0.0004873374,0.0002608908,0.004846638,0.006059395,0.0009982267,0.05170619,0.1271417],"study_design_scores_gemma":[0.1722472,0.06973274,0.6889935,0.000741976,0.01407407,0.001057938,0.0002870915,0.01830701,0.003199163,0.004530448,0.02666442,0.0001646287],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9691714,0.005498862,0.001522147,0.001828253,0.0004437805,0.0009849994,0.01484972,0.0001858098,0.005515006],"genre_scores_gemma":[0.9674299,0.001455907,0.001591829,0.0008766089,0.0008164523,0.001068834,0.02420831,0.00003384843,0.002518234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005534154,"threshold_uncertainty_score":0.01851356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.351723897370684,"score_gpt":0.3793038996512906,"score_spread":0.02758000228060653,"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."}}