{"id":"W4403822182","doi":"10.1093/eurheartj/ehae666.3452","title":"Prospective evaluation of an AI algorithm for real-time LVEF assessment in acute coronary syndrome using left coronary angiograms: the CathEF multicenter study","year":2024,"lang":"en","type":"article","venue":"European Heart Journal","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Heart Institute; Montreal Heart Institute","funders":"","keywords":"Medicine; Ejection fraction; Coronary angiography; Cardiology; Acute coronary syndrome; Internal medicine; Prospective cohort study; Algorithm; Myocardial infarction; Heart failure","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01013016,0.0007137518,0.0008047359,0.001274902,0.0003904832,0.001192208,0.0008612727,0.0008452346,0.0006163818],"category_scores_gemma":[0.02128614,0.0003676488,0.0004837314,0.0006080478,0.0004806133,0.0008617452,0.0008658263,0.0005158121,0.0001605556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006692545,"about_ca_system_score_gemma":0.0006066721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001538638,"about_ca_topic_score_gemma":0.0009386216,"domain_scores_codex":[0.9954578,0.003001519,0.0002506894,0.0006211964,0.0005031979,0.0001656573],"domain_scores_gemma":[0.9875936,0.005180423,0.002219591,0.001502093,0.002500542,0.001003756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01958744,0.001565903,0.9352028,0.00009196874,0.0004381942,0.0001200476,0.0002638128,0.001616105,0.002745317,0.0001588471,0.001318196,0.03689142],"study_design_scores_gemma":[0.002748282,0.01297244,0.9425744,0.000041411,0.0003477497,0.0007581349,0.000338928,0.03615902,0.002463821,0.0001274508,0.00139177,0.00007664975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964854,0.0002039605,0.002017272,0.00006249764,0.00001383413,0.0003919987,0.0005088185,0.00005573364,0.0002606029],"genre_scores_gemma":[0.9906261,0.00005812293,0.007613225,0.00004812691,0.00003920092,0.0005383056,0.0009760004,0.00002111207,0.00007985153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01013016,"threshold_uncertainty_score":0.05357403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04328484148894462,"score_gpt":0.391578191548305,"score_spread":0.3482933500593604,"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."}}