{"id":"W3099824897","doi":"10.1002/emp2.12277","title":"Artificial intelligence in emergency medicine: A scoping review","year":2020,"lang":"en","type":"review","venue":"Journal of the American College of Emergency Physicians Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University Health Network; University of Toronto","funders":"","keywords":"CINAHL; Psychological intervention; Emergency department; MEDLINE; Medicine; Systematic review; Emergency medicine; Medical emergency; Psychiatry","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":[0.02410085,0.002001133,0.006039313,0.02916955,0.001608178,0.006882385,0.00265552,0.004713555,0.005371078],"category_scores_gemma":[0.09337885,0.001641013,0.006069721,0.02688807,0.002142926,0.005702437,0.003629389,0.002797484,0.001059318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005732453,"about_ca_system_score_gemma":0.02222986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005652528,"about_ca_topic_score_gemma":0.009743035,"domain_scores_codex":[0.9799254,0.008096428,0.006893774,0.0009353861,0.003640298,0.0005086513],"domain_scores_gemma":[0.9209039,0.06159399,0.008395915,0.001140261,0.007375863,0.0005900934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009861647,0.00003814552,0.000528505,0.8121206,0.001517123,0.0002196895,0.0007623522,0.0002923903,0.0001835028,0.002060149,0.009068036,0.1731108],"study_design_scores_gemma":[0.00002142009,0.00003782181,0.0005725877,0.964518,0.002214151,0.0001979815,0.0002930451,0.0000741868,0.00006164795,0.000726033,0.03126676,0.00001646938],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002070118,0.9973161,0.0002741101,0.0009371757,0.0002678561,0.0002782236,0.00009347915,0.000007672204,0.0006184546],"genre_scores_gemma":[0.002376597,0.9952118,0.0008299716,0.0005973511,0.0001856065,0.0005718381,0.0001171136,0.000005505206,0.0001043139],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02916955,"threshold_uncertainty_score":0.127459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2886269990965217,"score_gpt":0.52743025257819,"score_spread":0.2388032534816683,"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."}}