{"id":"W2802844958","doi":"10.1111/acem.13442","title":"Automated Pulmonary Embolism Risk Classification and Guideline Adherence for Computed Tomography Pulmonary Angiography Ordering","year":2018,"lang":"en","type":"article","venue":"Academic Emergency Medicine","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research and Materiel Command; School of Medicine, New York University; Agency for Healthcare Research and Quality; York University","keywords":"Medicine; Guideline; Concordance; Pulmonary embolism; Emergency department; Chart; Medical physics; Radiology; Emergency medicine; Internal medicine; Pathology; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.008903995,0.0003249091,0.0004451015,0.002000717,0.0002580561,0.001377611,0.0005121173,0.0005675347,0.0004906501],"category_scores_gemma":[0.06692252,0.000230554,0.0004927919,0.0009904607,0.000274116,0.0007841383,0.0007907588,0.0004853352,0.0002362225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006907402,"about_ca_system_score_gemma":0.0008154126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003302309,"about_ca_topic_score_gemma":0.004091138,"domain_scores_codex":[0.9882455,0.005229825,0.001604464,0.001355586,0.003239008,0.0003256391],"domain_scores_gemma":[0.9368637,0.03451697,0.01509019,0.003020376,0.009834063,0.0006748473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005134396,0.000203559,0.9079265,0.00009849021,0.0001641996,0.00006754436,0.0004413236,0.003932727,0.0009351185,0.0001437634,0.0009150853,0.08465818],"study_design_scores_gemma":[0.0000885855,0.0006914706,0.9174072,0.0001103716,0.0001442521,0.0004066456,0.0003366981,0.07642958,0.003013628,0.0004109702,0.0009072141,0.00005341821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896613,0.0002131002,0.007697818,0.0001722366,0.0000252453,0.0001456266,0.0003549125,0.0001696077,0.001560145],"genre_scores_gemma":[0.9896836,0.00005298086,0.009617751,0.00003923488,0.00001575139,0.0000636542,0.0004222043,0.000008436853,0.00009627754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008903995,"threshold_uncertainty_score":0.0470894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04320263350067489,"score_gpt":0.3481157332200175,"score_spread":0.3049130997193427,"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."}}