{"id":"W3123679449","doi":"10.1145/3429336","title":"Green Simulation with Database Monte Carlo","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Modeling and Computer Simulation","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control variates; Variance reduction; Computer science; Monte Carlo method; Variance (accounting); Convergence (economics); Reduction (mathematics); Idle; Database; Mathematical optimization; Simulation; Statistics; Mathematics; Monte Carlo molecular modeling","routes":{"ca_aff":true,"ca_fund":true,"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":[0.008880114,0.0008038059,0.001104901,0.001127917,0.0006224553,0.001746267,0.002234587,0.001779154,0.003180366],"category_scores_gemma":[0.02839337,0.0006353657,0.0009781679,0.001216769,0.001954024,0.001838493,0.001722922,0.001888311,0.0004557449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001535661,"about_ca_system_score_gemma":0.001845945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004436161,"about_ca_topic_score_gemma":0.002964951,"domain_scores_codex":[0.9947252,0.003434882,0.0001530789,0.0005749909,0.0008713655,0.0002405643],"domain_scores_gemma":[0.9721352,0.02169644,0.001146872,0.003394339,0.001274322,0.0003528916],"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":[0.0002887139,0.0001101808,0.00126346,0.00005847092,0.00005310107,0.0000432339,0.00008006683,0.8968866,0.001027021,0.08499527,0.0004749778,0.01471898],"study_design_scores_gemma":[0.00001824334,0.00002142397,0.00005677082,0.000003280159,0.000004181105,0.000004809899,0.000005170376,0.9859269,0.000437256,0.01323986,0.0002772588,0.000004995449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01770919,0.00009837589,0.9795007,0.0001275845,0.00002944951,0.0001130846,0.00006344609,0.0004204248,0.001937821],"genre_scores_gemma":[0.5630534,0.0001572357,0.4326513,0.00026616,0.00004301725,0.001029062,0.0002579625,0.0002274181,0.002314551],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008880114,"threshold_uncertainty_score":0.04696304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1120401573890475,"score_gpt":0.3269404755585381,"score_spread":0.2149003181694906,"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."}}