{"id":"W4415700663","doi":"10.1148/ryct.240568","title":"Artificial Intelligence–based Coronary Plaque Quantification Using Coronary CT Angiography: Current Insights and Future Directions","year":2025,"lang":"en","type":"review","venue":"Radiology Cardiothoracic Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"Coronary artery disease; Risk stratification; Coronary angiography; Clinical significance; Vulnerable plaque; Risk assessment; Patient care; CAD","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004999961,0.0007792287,0.002756584,0.001614156,0.0004353972,0.0000820326,0.0001715796,0.0002717729,0.00001168549],"category_scores_gemma":[0.0002183657,0.0007238091,0.001827601,0.001193293,0.0005306628,0.0001240594,0.0001006193,0.001188536,0.00001330037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004043932,"about_ca_system_score_gemma":0.001209587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002840661,"about_ca_topic_score_gemma":0.00000153012,"domain_scores_codex":[0.9962687,0.0007705859,0.001002149,0.001128074,0.0002676668,0.0005627523],"domain_scores_gemma":[0.9972603,0.001106164,0.0003727205,0.0008234219,0.0002022294,0.0002351407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003847227,0.0000822803,0.003390835,0.00710205,0.0006163364,0.0004813323,0.00005251479,0.00002604029,0.000002592777,0.0001819103,0.0004357854,0.9875898],"study_design_scores_gemma":[0.0001381788,0.00003960275,0.001241946,0.01143622,0.01008506,0.006453059,0.0001158359,0.001166476,0.000008235796,0.000133445,0.9684212,0.0007607215],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001200461,0.978529,0.01384597,0.0002028301,0.005281589,0.001323682,0.000170996,0.0002742171,0.0002517113],"genre_scores_gemma":[0.002127268,0.9923795,0.001793715,0.0001222515,0.002106961,0.0001445853,0.001219542,0.00009387492,0.00001227873],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9868291,"threshold_uncertainty_score":0.9995213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04628394885595958,"score_gpt":0.3761305773458594,"score_spread":0.3298466284898998,"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."}}