{"id":"W4304974837","doi":"10.2196/41503","title":"Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics’ Common Data Model","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Observational study; Medicine; Coronary artery disease; Informatics; Computed tomography; Radiology; Angiography; Computed tomography angiography; Cardiology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0102466,0.0004561028,0.0009550297,0.0009911224,0.0007108583,0.0009333409,0.001266219,0.0008332013,0.001010499],"category_scores_gemma":[0.0182824,0.0006153968,0.002165083,0.002586161,0.000329542,0.0006448652,0.001359581,0.001385833,0.0002299671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007158277,"about_ca_system_score_gemma":0.002047232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0203317,"about_ca_topic_score_gemma":0.01604243,"domain_scores_codex":[0.9924769,0.004078811,0.00067982,0.001238706,0.001036098,0.0004897376],"domain_scores_gemma":[0.9878243,0.003357799,0.003471162,0.003312152,0.001183568,0.000851062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00108389,0.000413247,0.9938025,0.00006201519,0.001488365,0.00007085404,0.00007777179,0.00065272,0.00009016379,0.0001610183,0.0005849284,0.001512557],"study_design_scores_gemma":[0.0007790726,0.00109796,0.9772185,0.00007447668,0.001813954,0.0002983716,0.0004222248,0.01640327,0.0001770251,0.0003733342,0.001305915,0.0000359049],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904619,0.0003130939,0.00304177,0.0001439008,0.00002539469,0.0002610408,0.005469779,0.00001373411,0.0002693692],"genre_scores_gemma":[0.9903291,0.000180405,0.002651619,0.00007904104,0.00002287472,0.0003878656,0.00616919,0.000005192283,0.0001746271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0203317,"threshold_uncertainty_score":0.05418986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1344300789227441,"score_gpt":0.376536632702434,"score_spread":0.2421065537796898,"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."}}