{"id":"W2144185040","doi":"10.12927/hcpol.2014.23809","title":"The Effect of Rostering with a Patient Enrolment Model on Emergency Department Utilization","year":2014,"lang":"en","type":"article","venue":"Healthcare policy","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Health and Long Term Care","funders":"","keywords":"Emergency department; Medical emergency; Medicine; Emergency medicine; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02615357,0.0009033195,0.001055869,0.0004240747,0.0005331484,0.001176117,0.001624187,0.0008859649,0.003582368],"category_scores_gemma":[0.04359123,0.000357327,0.002469995,0.0004327459,0.0005961666,0.0007748153,0.001456548,0.001431084,0.000200453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006561274,"about_ca_system_score_gemma":0.006936634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1320836,"about_ca_topic_score_gemma":0.08147359,"domain_scores_codex":[0.9886867,0.008453571,0.0003754587,0.0009588634,0.0005767262,0.0009487118],"domain_scores_gemma":[0.971449,0.0185337,0.005731029,0.001335413,0.001390401,0.00156056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03159033,0.002951665,0.7270268,0.0004198218,0.004247712,0.0002540294,0.0004933434,0.1881232,0.0005064878,0.003642502,0.002741615,0.03800247],"study_design_scores_gemma":[0.005686848,0.01974215,0.3019699,0.0001451955,0.003215497,0.00009975552,0.0005686138,0.6627861,0.0007441835,0.001953302,0.002994331,0.00009422719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927703,0.0002085132,0.003855244,0.0008143093,0.00004454897,0.0005438914,0.000667632,0.00003914724,0.001056438],"genre_scores_gemma":[0.9973421,0.00006108367,0.001370167,0.00008487982,0.00001156525,0.0001704358,0.0003366992,0.0000032441,0.000619893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1320836,"threshold_uncertainty_score":0.2626294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02707459333271023,"score_gpt":0.3474405958394353,"score_spread":0.320366002506725,"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."}}