{"id":"W2115251731","doi":"10.5555/1161734.1161962","title":"Simulation input updating using Bayesian techniques","year":2004,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Bayesian probability; Data mining; Quality (philosophy); Term (time); Machine learning; Artificial intelligence","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":[0.006629895,0.001186247,0.001511236,0.002231425,0.0008915599,0.002496748,0.002957207,0.001674392,0.006575248],"category_scores_gemma":[0.04806171,0.001533576,0.001223868,0.00176921,0.0008739271,0.003784474,0.002345597,0.002836009,0.001613395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536291,"about_ca_system_score_gemma":0.002375934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008499071,"about_ca_topic_score_gemma":0.007882955,"domain_scores_codex":[0.9946851,0.002537178,0.0003156445,0.0006155817,0.001614466,0.0002321444],"domain_scores_gemma":[0.9798682,0.01308852,0.001029844,0.002229391,0.00353485,0.00024922],"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":[0.0001236744,0.00008861667,0.001224338,0.0000910991,0.00008927764,0.0000780777,0.0001692012,0.8256345,0.001127085,0.05438595,0.002087281,0.1149009],"study_design_scores_gemma":[0.0000219474,0.00001855576,0.0001246167,0.00001967671,0.00001541043,0.00001949659,0.00001008789,0.9734111,0.0006348426,0.02351059,0.002197995,0.00001570272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001725138,0.00005923177,0.9956086,0.0001023007,0.00002547767,0.00004920485,0.00004773147,0.0005857495,0.001796598],"genre_scores_gemma":[0.227544,0.0004799849,0.7664022,0.0002004515,0.0001279073,0.0005753539,0.0005661492,0.0005899312,0.003513996],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008499071,"threshold_uncertainty_score":0.03506267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02076875667434968,"score_gpt":0.2784804553709493,"score_spread":0.2577116986965996,"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."}}