{"id":"W4384945457","doi":"10.1016/j.jcct.2023.05.137","title":"Comparison Of AI-based Coronary CTA Interpretation And QCA For Coronary Stenosis Evaluation","year":2023,"lang":"en","type":"article","venue":"Journal of cardiovascular computed tomography","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"Medicine; Coronary artery disease; Coronary angiography; Stenosis; Context (archaeology); Gold standard (test); Radiology; Cardiology; Internal medicine; Angiography; Diagnostic accuracy; Myocardial infarction","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":[],"consensus_categories":[],"category_scores_codex":[0.001642135,0.0001602404,0.0009015057,0.0008540853,0.00006106137,0.0000248946,0.00008285397,0.00007666088,0.000003609694],"category_scores_gemma":[0.0002863016,0.0001483641,0.001738187,0.0006967279,0.00009776779,0.0001059913,0.00003015763,0.0002225135,9.154833e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004412655,"about_ca_system_score_gemma":0.0001918432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004900538,"about_ca_topic_score_gemma":2.744071e-7,"domain_scores_codex":[0.9978541,0.0002042666,0.0006309394,0.0001847315,0.0009517328,0.0001742267],"domain_scores_gemma":[0.9973223,0.0005082829,0.0002964409,0.000279458,0.001461426,0.0001321441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001404273,0.0003375794,0.7044756,0.0006538489,0.008579071,0.0001035855,0.0004590057,0.1115109,0.0003693961,0.00002388289,0.01139466,0.1606882],"study_design_scores_gemma":[0.007678568,0.001205746,0.8157122,0.0006648586,0.006008886,0.0002361698,0.000225078,0.1642997,0.001336758,0.0001877927,0.002277667,0.0001666965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8355271,0.02417878,0.1378325,0.0004881734,0.0009436822,0.0008479115,0.00003213591,0.0000590952,0.00009063048],"genre_scores_gemma":[0.9952709,0.0001161917,0.00416911,0.0001267587,0.0001826293,0.00001437815,0.00009258537,0.00002585962,0.000001581339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1605215,"threshold_uncertainty_score":0.6050114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02913609021947626,"score_gpt":0.3252512134100913,"score_spread":0.296115123190615,"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."}}