{"id":"W2082820221","doi":"10.1115/detc2008-49991","title":"Enhanced Multi-Agent Normal Sampling Technique for Global Optimization","year":2008,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Manitoba","funders":"","keywords":"Mathematical optimization; Computer science; Sampling (signal processing); Global optimization; Standard deviation; Normal distribution; Algorithm; Mathematics; Statistics","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":[0.0003411403,0.000126966,0.0001443693,0.00008596906,0.0002582193,0.00008808908,0.0006542254,0.00007258094,0.00008914281],"category_scores_gemma":[0.0002817248,0.0001193201,0.00006435696,0.0005528467,0.00004426026,0.0003769725,0.0002121521,0.00006931488,0.00002518008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001034645,"about_ca_system_score_gemma":0.0001578594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001131322,"about_ca_topic_score_gemma":0.000001748637,"domain_scores_codex":[0.9985803,0.00005187277,0.0002869149,0.0003950746,0.0003441868,0.0003415848],"domain_scores_gemma":[0.9988968,0.00008708219,0.00007079714,0.0004096055,0.0003979535,0.0001377125],"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":[0.00001461422,0.0002124781,0.00008983691,0.00002605888,0.0000218189,0.000005543362,0.0001364119,0.9692118,0.002098579,0.01825201,0.0005328707,0.009397995],"study_design_scores_gemma":[0.0005308209,0.00005311994,0.0001217186,0.000004629315,0.000001843339,0.0000270287,0.000004192151,0.9838528,0.01465035,0.0000981766,0.0005041259,0.0001511722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002498367,0.00001621441,0.9965345,0.0001680346,0.0001887811,0.0008396338,0.000005487296,0.0002583179,0.001964022],"genre_scores_gemma":[0.009697101,0.00003621255,0.9886208,0.0001416896,0.00004236445,0.0002450711,0.0000132273,0.000009352951,0.001194216],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01815383,"threshold_uncertainty_score":0.4865734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07399700246656397,"score_gpt":0.3443902893398757,"score_spread":0.2703932868733117,"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."}}