{"id":"W4410733729","doi":"10.1016/j.jstrokecerebrovasdis.2025.108359","title":"Arterial brain calcium (ABC) volume - A novel radiological marker of atherosclerotic risk and future stroke risk on non-contrast CT","year":2025,"lang":"en","type":"article","venue":"Journal of Stroke and Cerebrovascular Diseases","topic":"Cerebrovascular and Carotid Artery Diseases","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Alberta; University of Calgary","funders":"Eisai; Government of Canada; Servier; Fondation Brain Canada; Alberta Innovates; Canadian Cardiovascular Society; Alexion Pharmaceuticals; Biogen","keywords":"Radiological weapon; Contrast (vision); Medicine; Stroke (engine); Stroke risk; Cardiology; Radiology; Internal medicine; Ischemic stroke; Computer science; Artificial intelligence; Ischemia; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005092334,0.0003424431,0.0002358507,0.001776485,0.0002549639,0.001094453,0.0006173521,0.0003248453,0.001457674],"category_scores_gemma":[0.002678116,0.0001855563,0.0002325515,0.00108124,0.0005159982,0.0003325095,0.0003339027,0.0002847706,0.0001560829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009275092,"about_ca_system_score_gemma":0.001030759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06520018,"about_ca_topic_score_gemma":0.110833,"domain_scores_codex":[0.9996032,0.00004397618,0.00003450726,0.00007241414,0.0002028027,0.00004304457],"domain_scores_gemma":[0.9986897,0.0001790561,0.0006592247,0.0000794994,0.000306729,0.00008586864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001469539,0.00001311157,0.9917508,0.00003814652,0.0001080981,0.0001060648,0.00008906703,0.0003347181,0.001110765,0.00008444778,0.0002775127,0.005940369],"study_design_scores_gemma":[0.000005890687,0.00002701279,0.9975922,0.00001164544,0.00005126546,0.0006441774,0.00006870048,0.0009308824,0.000312157,0.00009291497,0.0002583951,0.000004615634],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958413,0.0007604592,0.0008371357,0.00006390815,0.000007721268,0.00002616444,0.0005817568,0.00003994257,0.001841549],"genre_scores_gemma":[0.9983474,0.0001585775,0.00075503,0.00001237325,0.0000104551,0.000008546383,0.000382955,0.000006155165,0.0003184782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06520018,"threshold_uncertainty_score":0.1296414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005357437120195339,"score_gpt":0.2231481765432495,"score_spread":0.2177907394230541,"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."}}