{"id":"W1915513264","doi":"10.5430/jha.v4n5p40","title":"Specialized fast track: a sustainable model to improve emergency department patient flow","year":2015,"lang":"en","type":"article","venue":"Journal of Hospital Administration","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overcrowding; Fast track; Medicine; Emergency department; Triage; Staffing; Crowding; Medical emergency; Emergency medicine; Nursing; Surgery","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":[0.004480376,0.0005721273,0.000206404,0.0009802983,0.001214158,0.001825463,0.002017254,0.0009071199,0.002987632],"category_scores_gemma":[0.00635601,0.0002373147,0.0006480172,0.0006445625,0.0007271008,0.002186141,0.00433429,0.0006886757,0.0005581665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001825762,"about_ca_system_score_gemma":0.007456527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003291817,"about_ca_topic_score_gemma":0.007041009,"domain_scores_codex":[0.9977624,0.0009931793,0.00009705734,0.0002676187,0.0005534743,0.0003262451],"domain_scores_gemma":[0.9972152,0.0004115604,0.0004461946,0.0002621193,0.0005739512,0.001091053],"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":[0.001042782,0.006553542,0.18299,0.0009836847,0.0002633884,0.001357832,0.005001946,0.08776163,0.007920227,0.0185912,0.04122877,0.646305],"study_design_scores_gemma":[0.002065397,0.02618549,0.1893792,0.001387136,0.0004551115,0.002981612,0.0215473,0.4744231,0.01263208,0.0577441,0.210745,0.0004545472],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7366147,0.00043831,0.2251506,0.01136671,0.0004950681,0.002428921,0.0005069621,0.001865063,0.02113374],"genre_scores_gemma":[0.8212399,0.0004397254,0.1696253,0.00150348,0.0001717549,0.001004567,0.0006260155,0.00009467189,0.00529468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004480376,"threshold_uncertainty_score":0.02369475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673478118202109,"score_gpt":0.2928352675398165,"score_spread":0.2761004863577954,"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."}}