{"id":"W4413259642","doi":"10.1016/j.hlc.2025.06.034","title":"A Novel, Fully Automated Stenosis, High Risk fEature and Dispersion (CAD-SHRED) Score on CTCA Provides Robust Prediction of Short-Term MACE","year":2025,"lang":"en","type":"article","venue":"Heart Lung and Circulation","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Western University; McMaster University; University of Alberta","funders":"","keywords":"Medicine; Mace; CAD; Cardiology; Feature (linguistics); Internal medicine; Term (time); Engineering drawing; Engineering","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":[0.000802449,0.000646434,0.001154072,0.001384907,0.000264698,0.001200781,0.0004903799,0.0007500988,0.0008433979],"category_scores_gemma":[0.002465642,0.0002299193,0.0004832102,0.0005733168,0.0001739006,0.0004842895,0.0006121379,0.0005393596,0.0004892171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002269914,"about_ca_system_score_gemma":0.0005178449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003266928,"about_ca_topic_score_gemma":0.007362413,"domain_scores_codex":[0.9995234,0.00007736101,0.0000334242,0.0001709767,0.00013851,0.00005635884],"domain_scores_gemma":[0.9991919,0.0002664702,0.0001352706,0.00007907107,0.000233008,0.00009427662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002509634,0.0007017198,0.560244,0.0001986593,0.0009503392,0.000498158,0.00009018415,0.02404225,0.02592877,0.0006785967,0.009417878,0.3747398],"study_design_scores_gemma":[0.0002373013,0.00100874,0.4545616,0.00005048805,0.000585678,0.001448191,0.00007533286,0.5272737,0.008888851,0.001747952,0.003938585,0.0001835173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.895758,0.002806105,0.09067805,0.000455971,0.0002390369,0.0001503459,0.00504396,0.001942614,0.002925854],"genre_scores_gemma":[0.9813949,0.0002645865,0.01429653,0.0001355365,0.0002125764,0.00005893163,0.002475833,0.00006193895,0.001099167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003266928,"threshold_uncertainty_score":0.006495833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280493798807613,"score_gpt":0.2581267963521022,"score_spread":0.245321858364026,"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."}}