{"id":"W1998532326","doi":"10.1111/j.1524-4733.2010.00775.x","title":"Discrete Event Simulation: The Preferred Technique for Health Economic Evaluations?","year":2010,"lang":"en","type":"article","venue":"Value in Health","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":149,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Discrete event simulation; Event (particle physics); Computer science; Markov chain; Health care; Markov model; Risk analysis (engineering); Management science; Operations research; Data science; Machine learning; Simulation; Medicine; Economics; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03374426,0.0007789871,0.002193639,0.001255364,0.0004021943,0.004376808,0.002134407,0.002036439,0.0113055],"category_scores_gemma":[0.1529623,0.0006497221,0.001201655,0.002699796,0.001366435,0.005687875,0.001486135,0.005088851,0.001451334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00071664,"about_ca_system_score_gemma":0.002699182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002807081,"about_ca_topic_score_gemma":0.002692269,"domain_scores_codex":[0.9801587,0.01737109,0.0005668994,0.0004845175,0.001241291,0.0001774645],"domain_scores_gemma":[0.9113651,0.07689153,0.00344332,0.004550714,0.002783079,0.000966223],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001845788,0.0005000887,0.01115289,0.001797368,0.001604241,0.0002364351,0.0006295528,0.2922314,0.0007517484,0.4033265,0.03865238,0.2472717],"study_design_scores_gemma":[0.000549612,0.0003337706,0.0009390665,0.0008180715,0.0001869721,0.0001286788,0.0004483418,0.5960529,0.0006339385,0.3772117,0.02259392,0.0001029764],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01134271,0.001584983,0.9661923,0.01341684,0.0009008825,0.0001792999,0.0007384606,0.0004869644,0.005157622],"genre_scores_gemma":[0.4864067,0.005489934,0.4974234,0.00365749,0.0009603184,0.0008641621,0.000810218,0.0007054929,0.003682314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9662557,"threshold_uncertainty_score":0.1784589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1450206997427288,"score_gpt":0.518710997552107,"score_spread":0.3736902978093782,"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."}}