{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003695704,0.0001450493,0.0001768542,0.0001528397,0.0002413836,0.0001603735,0.0001803561,0.00006734364,0.00002181322],"category_scores_gemma":[0.00008927509,0.0001130286,0.00005060403,0.0003811244,0.0000214646,0.0003445115,0.00001304993,0.0001521712,0.000012549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002397726,"about_ca_system_score_gemma":0.00004488676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003556699,"about_ca_topic_score_gemma":0.00001976265,"domain_scores_codex":[0.9984508,0.00008794298,0.0003248649,0.0004766583,0.0005124094,0.0001473711],"domain_scores_gemma":[0.9978881,0.0009404987,0.00005100203,0.0006607638,0.0003722172,0.00008743996],"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":[0.0000376177,0.00003732644,0.00002335517,0.000005269562,0.00001553077,0.000005388779,0.0002007688,0.9323357,0.000007305932,0.00005097763,0.000002787754,0.06727797],"study_design_scores_gemma":[0.0004100256,0.00006893366,0.00007950935,0.00003952264,0.00002874029,0.000006294854,0.00004075753,0.9963533,0.00001500448,0.002705588,0.0001030268,0.0001493165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06112189,0.00005886414,0.9382434,0.0001997433,0.0001561638,0.0001000542,0.00001255163,0.00008754482,0.0000198065],"genre_scores_gemma":[0.9306323,0.000006469511,0.0689811,0.0001088931,0.00007136611,0.000004713321,0.000007088639,0.00001301832,0.0001750913],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8695104,"threshold_uncertainty_score":0.4609173,"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."}}