{"id":"W4392906101","doi":"10.32920/25412860","title":"The Use of Simulation in Support of Managerial Decision Making in Hospitals","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"","keywords":"Intuition; Human resources; Health care; Process (computing); Quality (philosophy); Business; Risk analysis (engineering); Human resource management; Christian ministry; Decision quality; Affect (linguistics); Decision-making; Process management; Knowledge management; Computer science; Psychology; Marketing; Team effectiveness","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":[0.003099909,0.0008987213,0.0008310874,0.0006639396,0.0006894834,0.002373952,0.001314667,0.001733254,0.005926115],"category_scores_gemma":[0.01646869,0.0005101726,0.0005824527,0.0006084963,0.0006831601,0.001090336,0.001571204,0.001608261,0.0004910114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170431,"about_ca_system_score_gemma":0.002393502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01001203,"about_ca_topic_score_gemma":0.007181079,"domain_scores_codex":[0.9981295,0.001408799,0.00009870956,0.0001164279,0.0001518845,0.00009464891],"domain_scores_gemma":[0.9674658,0.02932272,0.0007345256,0.0007946282,0.0009376631,0.0007447882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005022586,0.0003144427,0.00402732,0.0001160909,0.00006209934,0.0001742388,0.0004377085,0.9701516,0.0007843765,0.005540185,0.001360659,0.01652894],"study_design_scores_gemma":[0.00007092239,0.0000560723,0.000277376,0.00003156661,0.000009032167,0.00001265454,0.00009287299,0.9927038,0.0004561596,0.00509826,0.001177581,0.00001381045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4520151,0.0008834185,0.49712,0.004620768,0.0006903692,0.0008081192,0.001392147,0.004943612,0.03752652],"genre_scores_gemma":[0.9020086,0.0003212466,0.09459815,0.0002254646,0.00006923138,0.0003310046,0.0004567933,0.0001372704,0.001852319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01001203,"threshold_uncertainty_score":0.01990753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1344749958658387,"score_gpt":0.4912809691763558,"score_spread":0.3568059733105172,"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."}}