{"id":"W3134103604","doi":"","title":"Can Pregnancy-Adapted Algorithms Avoid Diagnostic Imaging for Pulmonary Embolism?","year":2020,"lang":"en","type":"article","venue":"62nd ASH Annual Meeting and Exposition","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Centre of Excellence for Women's Health; University of British Columbia","funders":"","keywords":"Medicine; Pulmonary embolism; D-dimer; Radiology; Pulmonary angiography; Medical imaging; Pre- and post-test probability; Population; Venous thrombosis; Medical diagnosis; Pregnancy; Thrombosis; Angiography; Surgery","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":[0.005592555,0.0007087225,0.0006736658,0.0008701116,0.0003391773,0.001955683,0.001745823,0.001391558,0.002410197],"category_scores_gemma":[0.05687304,0.0003274881,0.0005385838,0.0005832929,0.0006129777,0.002392753,0.0008877423,0.001728204,0.001093942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0010867,"about_ca_system_score_gemma":0.001940653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00337094,"about_ca_topic_score_gemma":0.005002605,"domain_scores_codex":[0.9964624,0.002365305,0.0002869703,0.0003340146,0.000403151,0.000148161],"domain_scores_gemma":[0.9929993,0.004248708,0.0008263144,0.0004864944,0.001044207,0.0003949913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001049133,0.0004467597,0.1167047,0.0002671678,0.0002569259,0.0003929698,0.0005495404,0.01142883,0.0007123993,0.005510812,0.01944469,0.843236],"study_design_scores_gemma":[0.003247882,0.00401755,0.17936,0.003734736,0.001271127,0.009063421,0.003785844,0.4888508,0.004294209,0.1459453,0.155998,0.0004311639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4189573,0.04347856,0.3254393,0.1567839,0.003401254,0.002123638,0.0009161136,0.004961604,0.04393833],"genre_scores_gemma":[0.7059982,0.006672549,0.2754613,0.008040196,0.0006272905,0.0005192311,0.000541308,0.0002052798,0.001934699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005592555,"threshold_uncertainty_score":0.0295766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334905666541249,"score_gpt":0.2461673316922483,"score_spread":0.2328182750268358,"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."}}