{"id":"W2024977848","doi":"10.4018/jhisi.2013070104","title":"Applying Discrete Event Simulation (DES) in Healthcare","year":2013,"lang":"en","type":"article","venue":"International Journal of Healthcare Information Systems and Informatics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Discrete event simulation; Capacity planning; Network planning and design; Health care; Event (particle physics); Computer science; Process (computing); Operations research; Business; Simulation; Engineering; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001948263,0.0001846433,0.0003959602,0.0007799098,0.0004166626,0.0002050564,0.0002468171,0.0002547405,0.00004275421],"category_scores_gemma":[0.0004626964,0.0001525683,0.00006536747,0.0002929337,0.00004312644,0.005297291,0.00007477409,0.0007364422,0.0001004074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006704546,"about_ca_system_score_gemma":0.0006229599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004846253,"about_ca_topic_score_gemma":0.0001705349,"domain_scores_codex":[0.9945576,0.0003256751,0.00386688,0.00006861217,0.0007989509,0.0003823471],"domain_scores_gemma":[0.9931594,0.0003090113,0.001975207,0.0001578603,0.004117658,0.000280885],"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":[0.00026636,0.00009192869,0.2784785,0.004685551,0.0001549153,0.000008335537,0.08560482,0.3886818,0.00001041144,0.04978858,0.001492629,0.1907362],"study_design_scores_gemma":[0.002761412,0.000327083,0.03122055,0.00284725,0.00001080419,0.0001081317,0.04607827,0.8362986,0.000002500182,0.0008266212,0.07915103,0.0003677339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6942698,0.002063143,0.2414619,0.03596501,0.01119593,0.01031008,0.0002571931,0.0001643823,0.004312507],"genre_scores_gemma":[0.9921329,0.0007257491,0.003845306,0.002620546,0.0002957085,0.00022881,0.0000960676,0.00001102502,0.00004390223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4476168,"threshold_uncertainty_score":0.7326117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04401978932451056,"score_gpt":0.4133545863849934,"score_spread":0.3693347970604829,"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."}}