{"id":"W2835082446","doi":"10.2196/medinform.9957","title":"A Computerized Method for Measuring Computed Tomography Pulmonary Angiography Yield in the Emergency Department: Validation Study","year":2018,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality","keywords":"Medicine; Emergency department; Pulmonary embolism; Radiology; Pulmonary angiography; Angiography; Computed tomography angiography; Computed tomography; Radiological weapon; Malignancy; Surgery; 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":[0.01863408,0.0006310729,0.0003983361,0.001937178,0.000338294,0.0009737316,0.001323214,0.0009382889,0.001006844],"category_scores_gemma":[0.09464317,0.0003949973,0.0008636666,0.001550782,0.0007713888,0.001019142,0.000997139,0.0005806164,0.0003585947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001056078,"about_ca_system_score_gemma":0.001339571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001997206,"about_ca_topic_score_gemma":0.001988045,"domain_scores_codex":[0.9815964,0.009086796,0.002693205,0.001588869,0.004692288,0.0003424149],"domain_scores_gemma":[0.8862461,0.05644165,0.02493171,0.009814345,0.02166299,0.0009032749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000652991,0.0006028453,0.9863657,0.00006768796,0.0002113486,0.0000626188,0.0002844909,0.0003986976,0.0005857265,0.0001113989,0.000233031,0.0104235],"study_design_scores_gemma":[0.0002339336,0.003333591,0.983779,0.00007852335,0.0002132891,0.0009434657,0.0003062932,0.007852658,0.001796003,0.0001137689,0.001322597,0.00002678868],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921302,0.0002586918,0.004850744,0.00007253139,0.00004054474,0.0007364863,0.0006248231,0.00003885459,0.001247023],"genre_scores_gemma":[0.9914846,0.0001129158,0.006430894,0.00009519766,0.00004780384,0.0005538826,0.001058214,0.00001584353,0.0002007474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01863408,"threshold_uncertainty_score":0.09854764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04108744437497218,"score_gpt":0.3386086738666181,"score_spread":0.2975212294916459,"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."}}