{"id":"W2124701820","doi":"10.1161/circoutcomes.113.000139","title":"Frequency, Predictors, and Consequences of Crossing Over to Revascularization Within 12 Months of Randomization to Optimal Medical Therapy in the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) Trial","year":2013,"lang":"en","type":"article","venue":"Circulation Cardiovascular Quality and Outcomes","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research","keywords":"Medicine; Revascularization; Hazard ratio; Angina; Percutaneous coronary intervention; Randomized controlled trial; Internal medicine; Unstable angina; Myocardial infarction; Cardiology; Coronary artery disease; Odds ratio; Proportional hazards model; Surgery; Confidence interval","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008728731,0.0002043797,0.0009731393,0.0002198553,0.0001491989,0.00009784257,0.00009018248,0.0001945723,0.00004189379],"category_scores_gemma":[0.00850481,0.0001462595,0.0004987939,0.0002926741,0.000319624,0.0002834132,0.00004429289,0.00016801,5.363696e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004351352,"about_ca_system_score_gemma":0.0001819118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000980529,"about_ca_topic_score_gemma":0.0001027275,"domain_scores_codex":[0.9951065,0.001707526,0.001449535,0.0004197629,0.00116329,0.0001534317],"domain_scores_gemma":[0.9973637,0.00108955,0.0004571669,0.0004430617,0.0004932854,0.000153205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007907007,0.000166725,0.9726287,0.000162374,0.0007942812,0.000003894558,0.004362884,0.001819158,0.0001169383,0.0004918912,0.00000889436,0.01865356],"study_design_scores_gemma":[0.02963165,0.0001611463,0.9642908,0.000360486,0.00051594,0.00001798743,0.0009463299,0.003394582,0.00004979599,0.0004717055,0.00001084346,0.0001487102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778701,0.002381106,0.01454772,0.001172857,0.0002023136,0.003780579,0.00001103431,0.00001623979,0.00001806563],"genre_scores_gemma":[0.9974822,0.0006086911,0.001210914,0.0003953585,0.00006159173,0.0001499595,0.00007270103,0.00001427522,0.000004311565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02884095,"threshold_uncertainty_score":0.999847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09119262044506743,"score_gpt":0.3991639441701889,"score_spread":0.3079713237251214,"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."}}