{"id":"W4307550129","doi":"10.3389/fcvm.2022.994483","title":"Comparison of conventional scoring systems to machine learning models for the prediction of major adverse cardiovascular events in patients undergoing coronary computed tomography angiography","year":2022,"lang":"en","type":"article","venue":"Frontiers in Cardiovascular Medicine","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Tehran Heart Center","keywords":"Medicine; Mace; Confidence interval; Revascularization; Myocardial infarction; Internal medicine; Cardiology; Hazard ratio; Radiology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01181646,0.00110328,0.0008220251,0.002367351,0.0002326176,0.001103671,0.0007834828,0.0006724352,0.000867487],"category_scores_gemma":[0.0246696,0.0002245874,0.000859208,0.0009747852,0.0003350165,0.001013641,0.0008563636,0.0007335826,0.0004017084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000587664,"about_ca_system_score_gemma":0.0006499373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001366381,"about_ca_topic_score_gemma":0.00136287,"domain_scores_codex":[0.9954116,0.002751432,0.0004002226,0.0004995298,0.0007288613,0.0002083844],"domain_scores_gemma":[0.9839012,0.01048033,0.001957182,0.001037999,0.002059373,0.0005638651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003016615,0.0005227429,0.8606079,0.0001721531,0.001384661,0.0001099653,0.0001596756,0.04145526,0.0006545095,0.0003947956,0.002058731,0.08946317],"study_design_scores_gemma":[0.0003332688,0.003717348,0.2723836,0.0001081827,0.0004910343,0.0004172074,0.0002145023,0.7186291,0.0009062935,0.001911947,0.0008172506,0.00007030243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731549,0.001505952,0.02302008,0.0003413222,0.0001237863,0.0001056086,0.0004602073,0.0002235795,0.001064578],"genre_scores_gemma":[0.9944547,0.0001552138,0.004808513,0.00004254452,0.00005385352,0.00003515918,0.0003339393,0.000009917973,0.0001062574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01181646,"threshold_uncertainty_score":0.06249213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01911091828670633,"score_gpt":0.2414769843434658,"score_spread":0.2223660660567595,"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."}}