{"id":"W3055608389","doi":"10.1016/j.jcmg.2020.05.039","title":"Impact of Early Revascularization on Major Adverse Cardiovascular Events in Relation to Automatically Quantified Ischemia","year":2020,"lang":"en","type":"article","venue":"JACC. Cardiovascular imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; University of Calgary","funders":"National Center for Advancing Translational Sciences; National Heart, Lung, and Blood Institute; National Institutes of Health","keywords":"Mace; Revascularization; Cardiology; Medicine; Internal medicine; Myocardial perfusion imaging; Myocardial infarction; Ischemia; Proportional hazards model; Perfusion; Percutaneous coronary intervention","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001284624,0.000402789,0.001400217,0.0004172604,0.00006660886,0.00002581527,0.0001765906,0.0001391596,0.00002247377],"category_scores_gemma":[0.00245089,0.0003940234,0.004188852,0.001187098,0.00004796924,0.0002515489,0.0001168275,0.0004487295,0.0001510399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003524843,"about_ca_system_score_gemma":0.000233818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004988074,"about_ca_topic_score_gemma":8.3496e-7,"domain_scores_codex":[0.9962082,0.0003000303,0.0007518295,0.0008003848,0.001433138,0.0005064094],"domain_scores_gemma":[0.997659,0.0001381588,0.0001162323,0.001316274,0.00034565,0.0004247143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005650751,0.0002303281,0.8820496,0.0005194558,0.007384079,0.0004483828,0.001594006,0.08633964,0.005732052,0.00007353222,0.0006449349,0.01441889],"study_design_scores_gemma":[0.004769943,0.0001893362,0.9838686,0.0006411695,0.002154519,0.00006582884,0.00009334959,0.005332464,0.001850447,0.00002165792,0.0005855346,0.0004271516],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598662,0.002511214,0.03367669,0.0005086598,0.0002059709,0.001452842,0.00002035853,0.0001979993,0.001560065],"genre_scores_gemma":[0.9964136,0.00004846366,0.002699354,0.0003238949,0.0002670722,0.00005063454,0.00008572797,0.00009721375,0.00001397052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.101819,"threshold_uncertainty_score":0.9998512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609829416689963,"score_gpt":0.2738359256384765,"score_spread":0.2577376314715769,"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."}}