{"id":"W4412436422","doi":"10.1016/j.cjco.2025.07.001","title":"Development and Validation of the CR-DECIDE Models to Predict Major Adverse Cardiovascular Events and Health Status in Stable Coronary Artery Disease","year":2025,"lang":"en","type":"article","venue":"CJC Open","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Centre for Advancing Health Outcomes; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Coronary artery disease; Disease; Internal medicine; Medicine; Cardiology; Cardiovascular health; Adverse effect","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.02799077,0.00165769,0.001224255,0.001717596,0.0008040878,0.002115573,0.00223675,0.001086979,0.00170128],"category_scores_gemma":[0.04892854,0.0008486976,0.002329815,0.0006604506,0.0007023404,0.0008897416,0.002091768,0.002584872,0.000499287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002655537,"about_ca_system_score_gemma":0.005970335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03163129,"about_ca_topic_score_gemma":0.02419753,"domain_scores_codex":[0.9917216,0.005393644,0.0004185226,0.001037208,0.0009979352,0.0004310726],"domain_scores_gemma":[0.9735811,0.01853094,0.001629804,0.00149702,0.004042667,0.0007184355],"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":[0.003978562,0.002515367,0.4795972,0.0002872077,0.002275107,0.0002810773,0.0005048586,0.3726684,0.0007495939,0.005101761,0.007241556,0.1247994],"study_design_scores_gemma":[0.0005191743,0.0009465531,0.03796563,0.00009639119,0.0003268406,0.0001380073,0.00009589387,0.9549517,0.0007395261,0.00274348,0.001430118,0.0000466989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8801883,0.0008375582,0.1071103,0.001768323,0.0002041033,0.001596669,0.003153424,0.0009400545,0.004201326],"genre_scores_gemma":[0.9439319,0.0001951546,0.0512735,0.000283214,0.00004532499,0.0007933688,0.002487751,0.00006260369,0.0009271503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03163129,"threshold_uncertainty_score":0.1480311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02901562164232684,"score_gpt":0.2989884316948361,"score_spread":0.2699728100525093,"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."}}