{"id":"W2269275143","doi":"10.1007/s00500-016-2060-y","title":"Multilevel framework for large-scale global optimization","year":2016,"lang":"en","type":"article","venue":"Soft Computing","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Benchmark (surveying); Computer science; Mathematical optimization; Global optimization; Scale (ratio); Artificial intelligence; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007296614,0.0001527881,0.0001872017,0.00007242602,0.0002959007,0.0001970816,0.000877874,0.0001067154,0.0000578891],"category_scores_gemma":[0.001477071,0.00011866,0.00008231204,0.0004429012,0.00003278162,0.0002907421,0.0004710898,0.00008600081,0.00005898664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001087715,"about_ca_system_score_gemma":0.000108065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002055736,"about_ca_topic_score_gemma":6.243592e-7,"domain_scores_codex":[0.9980791,0.00009337731,0.000328734,0.0005386813,0.0003967416,0.0005633238],"domain_scores_gemma":[0.9978797,0.00090951,0.0001393206,0.0005274384,0.0003854549,0.0001586111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001871392,0.0001936473,0.002357581,0.00005103002,0.00004499994,0.000006067841,0.0006170537,0.2214788,0.00003251723,0.2775879,0.00174165,0.49587],"study_design_scores_gemma":[0.0006210972,0.00003325201,0.0003372238,0.00006366112,0.000003158927,0.000005183032,0.00001262087,0.9867714,0.0000801868,0.01084652,0.00105338,0.0001722852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001252564,0.00003575584,0.9969348,0.001214668,0.000679963,0.0003398991,0.00002614418,0.0003471318,0.0002963841],"genre_scores_gemma":[0.05442591,0.000004505696,0.9448774,0.0002427429,0.0002260581,0.00001247952,0.000004445028,0.00001501684,0.0001913936],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7652926,"threshold_uncertainty_score":0.4838814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02775923828119252,"score_gpt":0.3267531708932578,"score_spread":0.2989939326120653,"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."}}