{"id":"W4386514288","doi":"10.1108/ijopm-12-2022-0792","title":"A complexity-based measure for emergency department crowding","year":2023,"lang":"en","type":"article","venue":"International Journal of Operations & Production Management","topic":"Emergency and Acute Care Studies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Overcrowding; Crowding; Computer science; Service (business); Complexity management; Measure (data warehouse); Operations research; Value (mathematics); Set (abstract data type); Operations management; Risk analysis (engineering); Business; Marketing; Data mining; Economics; Psychology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004818817,0.00009974525,0.0001477291,0.0004163901,0.0001815602,0.00002589108,0.0001316468,0.0000190964,0.0001386712],"category_scores_gemma":[0.00016863,0.00008604106,0.0001761145,0.0002761263,0.0000292527,0.0001667221,0.00003535822,0.00007926478,0.00002228826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001251924,"about_ca_system_score_gemma":0.00004782591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002143673,"about_ca_topic_score_gemma":0.0000137722,"domain_scores_codex":[0.9986827,0.0000230649,0.0004901541,0.0001612192,0.0005208847,0.0001219142],"domain_scores_gemma":[0.9982058,0.000009382583,0.0001146951,0.0001176803,0.001506062,0.00004632872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001249487,0.001227891,0.008435932,0.0003775548,0.005773379,0.0002083395,0.001150026,0.06228685,0.01010747,0.03356119,0.837148,0.03847393],"study_design_scores_gemma":[0.006842402,0.001239546,0.05428398,0.0008584315,0.001500032,0.0002739253,0.003757555,0.008680149,0.0146003,0.004637321,0.9026415,0.0006848694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4785053,0.00201306,0.1708738,0.2943363,0.04078205,0.0043959,0.0001502544,0.0003602998,0.008583109],"genre_scores_gemma":[0.9753479,0.0009963056,0.01737327,0.0003739214,0.001934062,0.0001398495,0.0001658386,0.0000222454,0.003646624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4968426,"threshold_uncertainty_score":0.3508652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07441527137737426,"score_gpt":0.3737803251894721,"score_spread":0.2993650538120978,"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."}}