{"id":"W4412705911","doi":"10.1016/j.jacadv.2025.102014","title":"Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT","year":2025,"lang":"en","type":"article","venue":"JACC Advances","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Université de Montréal; Montreal Heart Institute; University of Ottawa","funders":"Deutsche Forschungsgemeinschaft","keywords":"Medicine; Coronary artery disease; Chest pain; Pre- and post-test probability; Computed tomography angiography; Angina; Logistic regression; Internal medicine; Radiology; Coronary angiography; Fractional flow reserve; Cardiology; Angiography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01413174,0.001453288,0.00285915,0.002014064,0.0003006218,0.001857348,0.001224672,0.00129354,0.001496173],"category_scores_gemma":[0.0414344,0.000795885,0.01211302,0.002074863,0.0004223081,0.0009269384,0.001085722,0.001528517,0.0002291866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005849958,"about_ca_system_score_gemma":0.0006629681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003073118,"about_ca_topic_score_gemma":0.003019396,"domain_scores_codex":[0.9879561,0.00813101,0.000929122,0.001806224,0.0009611457,0.0002164329],"domain_scores_gemma":[0.9629553,0.02548246,0.006074655,0.002636345,0.002398084,0.0004531677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01435452,0.0001483298,0.79506,0.005716032,0.1254665,0.0002081477,0.0001392393,0.01143486,0.0005574333,0.0006397258,0.003145937,0.04312924],"study_design_scores_gemma":[0.00361359,0.003494335,0.5095076,0.002260585,0.4016508,0.001539498,0.0001227829,0.06665887,0.001421054,0.003899288,0.005623464,0.0002081078],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7252314,0.2317373,0.02735015,0.002771874,0.0008477924,0.0003106118,0.00599293,0.000741619,0.005016345],"genre_scores_gemma":[0.9875596,0.004417202,0.005522042,0.0003418714,0.0002744327,0.0001106512,0.00150949,0.0000412482,0.0002233992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01413174,"threshold_uncertainty_score":0.07473665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004741351864878255,"score_gpt":0.2411671910425474,"score_spread":0.2364258391776692,"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."}}