{"id":"W4387934174","doi":"10.1016/j.jcjd.2023.10.331","title":"MACHINE LEARNING-BASED APPROACH FOR PREDICTING POST-TREATMENT SURVIVAL FOR PATIENTS WITH CORONARY ARTERY DISEASE","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Hospital Edmonton","funders":"","keywords":"Medicine; Conventional PCI; Coronary artery disease; Percutaneous coronary intervention; Internal medicine; CAD; Cardiology; Disease; Left main coronary artery disease; Medical therapy; Artery; Medical history; Myocardial infarction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001992831,0.0006715005,0.0009638917,0.002365413,0.0004107013,0.001275494,0.0009204991,0.001201939,0.002329774],"category_scores_gemma":[0.006184872,0.0001437241,0.0009893238,0.001034317,0.0001799637,0.0006062652,0.0005191992,0.001378722,0.0006703374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006991692,"about_ca_system_score_gemma":0.0008867042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005588542,"about_ca_topic_score_gemma":0.005809413,"domain_scores_codex":[0.9992981,0.0002624381,0.00008259968,0.000147816,0.000111373,0.00009765867],"domain_scores_gemma":[0.9975162,0.001601936,0.0002259686,0.00008885639,0.0003920098,0.0001750324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001646001,0.001570497,0.7452704,0.0001326857,0.0007015466,0.0002781303,0.00008981953,0.06398778,0.001032403,0.0009584218,0.005772628,0.1785598],"study_design_scores_gemma":[0.00008744766,0.000754412,0.1286651,0.00006506161,0.0002765439,0.0003047997,0.0001794907,0.8644908,0.0006573886,0.003304679,0.001174226,0.00004009052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.93427,0.002244811,0.05055347,0.002599331,0.0003618374,0.0001986996,0.005132742,0.0004348304,0.004204229],"genre_scores_gemma":[0.9871578,0.0002512608,0.009071553,0.000109313,0.0001494699,0.00005623656,0.002326143,0.000009395439,0.0008688541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005588542,"threshold_uncertainty_score":0.01111203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01653654723113865,"score_gpt":0.2360090082293264,"score_spread":0.2194724609981878,"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."}}