{"id":"W2524364156","doi":"10.1136/bmjquality.u206156.w2532","title":"Improving Emergency Department flow through optimized bed utilization","year":2016,"lang":"en","type":"article","venue":"BMJ Quality Improvement Reports","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"University Health Network","keywords":"Emergency department; Triage; Staffing; Medicine; Quality management; Hospital bed; Medical emergency; PDCA; Turnaround time; Emergency medicine; Percentile; Operations management; Nursing; Management system; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.003417221,0.0003911341,0.0002679428,0.001017482,0.0005880371,0.001537347,0.0009828737,0.0004041934,0.00309491],"category_scores_gemma":[0.007445959,0.0002068648,0.0003603694,0.000797651,0.0003858254,0.001167776,0.001478607,0.0005544712,0.0004433357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001809457,"about_ca_system_score_gemma":0.005416527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00460113,"about_ca_topic_score_gemma":0.005841957,"domain_scores_codex":[0.9968754,0.001450609,0.0001597927,0.0002849833,0.0006410603,0.0005881455],"domain_scores_gemma":[0.9975528,0.0006311468,0.0006567299,0.000178216,0.0005111267,0.0004699667],"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":[0.0009365794,0.007022536,0.1106567,0.0009194142,0.00009456896,0.0002140322,0.004547775,0.04186508,0.01056986,0.009738173,0.0179901,0.7954451],"study_design_scores_gemma":[0.001763025,0.01810717,0.5974206,0.001250388,0.0004467099,0.0008124217,0.01864091,0.1735851,0.04597211,0.02263013,0.119061,0.0003104979],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8962972,0.0007690329,0.06263448,0.006771831,0.0001597999,0.001835643,0.0007227714,0.001443316,0.02936582],"genre_scores_gemma":[0.9674692,0.000235354,0.02964478,0.0004381988,0.00003955284,0.0003943834,0.0001906013,0.00004773218,0.001540092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00460113,"threshold_uncertainty_score":0.01807225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07332527224961234,"score_gpt":0.3924314482512563,"score_spread":0.319106176001644,"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."}}