{"id":"W4387338202","doi":"10.1016/j.cjca.2023.06.122","title":"INFLUENCE OF ESTIMATED CORONARY CALCIUM FROM SPECT MPI ON INITIATION OF MEDICAL THERAPY","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Calgary Laboratory Services","funders":"","keywords":"Medicine; Myocardial perfusion imaging; Coronary artery disease; Coronary artery calcium; Single-photon emission computed tomography; Cardiology; Perfusion; Internal medicine; Emission computed tomography; Mace; Spect imaging; Perfusion scanning; Radiology; Nuclear medicine; Myocardial infarction; Conventional PCI","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001950819,0.0003845801,0.001058388,0.0005224691,0.0004575592,0.001212841,0.0005270789,0.00112036,0.003527281],"category_scores_gemma":[0.02310109,0.0002247916,0.001679645,0.0006608954,0.0004440651,0.0005025493,0.0003997773,0.001753618,0.0004006002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007715028,"about_ca_system_score_gemma":0.001628929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01013302,"about_ca_topic_score_gemma":0.009219596,"domain_scores_codex":[0.9977424,0.0009159937,0.0001695602,0.0003629063,0.0004173984,0.0003916872],"domain_scores_gemma":[0.9764247,0.01794222,0.001724371,0.0008083392,0.00094256,0.002157796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01509429,0.0003971781,0.9696932,0.00005005309,0.0008990584,0.000846035,0.0001726683,0.0005794715,0.001572462,0.0001016437,0.0004724225,0.01012155],"study_design_scores_gemma":[0.00004641081,0.0007704662,0.9964877,0.00001624244,0.0006081997,0.0002447861,0.0000891212,0.001058427,0.0002349447,0.00006854796,0.000360316,0.00001489248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918786,0.001597378,0.0003107296,0.0006249876,0.0001194275,0.0000190756,0.000545784,0.00002620633,0.004877834],"genre_scores_gemma":[0.9987482,0.0002091792,0.0001098313,0.00007864048,0.0001174584,0.000006159093,0.0002355365,0.00001410375,0.0004808115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01013302,"threshold_uncertainty_score":0.0201481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04758350821578832,"score_gpt":0.3291719954749344,"score_spread":0.2815884872591461,"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."}}