{"id":"W4387996367","doi":"10.1093/ehjci/jead288","title":"Impact of myocardial perfusion and coronary calcium on medical management for coronary artery disease","year":2023,"lang":"en","type":"article","venue":"European Heart Journal - Cardiovascular Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health","keywords":"Medicine; Myocardial perfusion imaging; Coronary artery disease; Medical prescription; Cardiology; Internal medicine; Statin; Perfusion; Single-photon emission computed tomography; Perfusion scanning; Radiology; Pharmacology","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":[0.001015351,0.0002644337,0.0002692626,0.0005430262,0.0002696202,0.0005407378,0.0003755052,0.0004517807,0.002061589],"category_scores_gemma":[0.005864232,0.0001735885,0.0005015002,0.0008840477,0.0003436708,0.0003443361,0.0003646636,0.0005853014,0.0002390738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003251552,"about_ca_system_score_gemma":0.0004558649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002509966,"about_ca_topic_score_gemma":0.003962788,"domain_scores_codex":[0.9989663,0.0003483437,0.0001472706,0.0001475854,0.0002614401,0.0001290454],"domain_scores_gemma":[0.9952436,0.001255382,0.002771808,0.0001676563,0.000241752,0.0003196686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004019246,0.000009108901,0.9987458,0.000006917478,0.0000314996,0.00005084187,0.000005166185,0.00002659949,0.00007103819,0.000006460805,0.00002424317,0.0009821228],"study_design_scores_gemma":[0.000001302996,0.00003050157,0.9994205,0.000007906386,0.00002613382,0.0002732973,0.00001530508,0.0001319091,0.00003044344,0.00001022286,0.00005114095,0.000001417535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996908,0.001762971,0.0001455052,0.0002456109,0.00001298844,0.000004190783,0.0002954681,0.000005490879,0.0006197579],"genre_scores_gemma":[0.9993191,0.0003170309,0.0001076799,0.00003233074,0.00002791944,0.000002297514,0.0001381425,0.000001597621,0.00005393492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002509966,"threshold_uncertainty_score":0.006896675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02810387699817478,"score_gpt":0.3094535204221832,"score_spread":0.2813496434240084,"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."}}