{"id":"W2942615032","doi":"10.1017/cem.2019.138","title":"MP03: Strategies to minimize impact of electronic health record implementation on emergency department flow","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Staffing; Electronic health record; Emergency department; Referral; Emergency medicine; Medical emergency; Health care; Family medicine; Nursing","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":[0.03396724,0.0009246402,0.0005249727,0.00349781,0.002422652,0.00570014,0.006077545,0.00292557,0.02123998],"category_scores_gemma":[0.1562758,0.0007363324,0.001428034,0.002285825,0.0006586158,0.005581802,0.006751007,0.003503497,0.003560925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004341508,"about_ca_system_score_gemma":0.03191722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01948255,"about_ca_topic_score_gemma":0.02487336,"domain_scores_codex":[0.9731476,0.01378762,0.003164036,0.001283551,0.006576524,0.002040755],"domain_scores_gemma":[0.8737453,0.0631493,0.01705498,0.01067831,0.02593361,0.009438369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005901903,0.003687075,0.07076214,0.001838759,0.0002883299,0.0002456191,0.002542844,0.004289224,0.002389516,0.00653589,0.1163755,0.7904549],"study_design_scores_gemma":[0.001802761,0.007200202,0.4753219,0.009556314,0.001522149,0.001461493,0.02203436,0.07862377,0.02938442,0.02086852,0.3516341,0.0005900849],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3163481,0.002549802,0.2338677,0.2365925,0.003122329,0.02132937,0.006066345,0.02051073,0.159613],"genre_scores_gemma":[0.5767443,0.001530033,0.3530304,0.03133421,0.001310152,0.01174578,0.002702397,0.001002722,0.02060009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03396724,"threshold_uncertainty_score":0.1796381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2376992586715297,"score_gpt":0.5274316172157256,"score_spread":0.2897323585441959,"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."}}