{"id":"W2558678654","doi":"10.1109/cec.2016.7744130","title":"An superior tracking artificial bee colony for global optimization problems","year":2016,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Natural Science Foundation of China","keywords":"Artificial bee colony algorithm; Benchmark (surveying); Bees algorithm; Dimension (graph theory); Convergence (economics); Computer science; Global optimization; Mathematical optimization; Tracking (education); Population; Optimization problem; Artificial intelligence; Metaheuristic; 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":[0.0005702642,0.0001220912,0.0001476608,0.00007499348,0.0001763146,0.0004138178,0.0007503339,0.00007393076,0.000222399],"category_scores_gemma":[0.0003155083,0.00008554891,0.00004891261,0.0004237922,0.00005687679,0.001017152,0.00008992411,0.00003429392,0.00003583332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009831723,"about_ca_system_score_gemma":0.0001624083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001053854,"about_ca_topic_score_gemma":0.00001821726,"domain_scores_codex":[0.9983484,0.00009522313,0.0003147507,0.0004789724,0.0003829243,0.0003797165],"domain_scores_gemma":[0.9987944,0.0001361435,0.00006315511,0.000370419,0.0004580721,0.0001778243],"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":[0.00004457183,0.0003889932,0.000505353,0.00003297399,0.00003213121,0.000006067511,0.0002313171,0.2068388,0.006717337,0.2828588,0.001473094,0.5008705],"study_design_scores_gemma":[0.0004138897,0.0002118087,0.0001200086,0.000009641714,0.000003612135,0.000006072427,0.000008042695,0.9928809,0.001920481,0.003195884,0.001072452,0.0001571539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004269019,0.000009134692,0.9952855,0.00248672,0.0002243475,0.0006341028,0.00001652899,0.0002517947,0.0006649519],"genre_scores_gemma":[0.07200927,0.000009625646,0.9269412,0.0001624211,0.0001346213,0.000113192,0.000007553355,0.00001387624,0.0006082588],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7860422,"threshold_uncertainty_score":0.3990454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04813931615633445,"score_gpt":0.3261855864511146,"score_spread":0.2780462702947802,"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."}}