{"id":"W3120100312","doi":"10.1109/ssci47803.2020.9308550","title":"Enhancing SHADE and L-SHADE Algorithms Using Ordered Mutation","year":2020,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Benchmark (surveying); Differential evolution; Algorithm; Computer science; Population; Mathematical optimization; Reduction (mathematics); Algorithm design; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007551268,0.0008053558,0.0009568685,0.0009060653,0.0005321327,0.0007988434,0.001147268,0.0007994648,0.001564883],"category_scores_gemma":[0.002543566,0.0002605253,0.0007944612,0.000690655,0.0005260404,0.0009345983,0.001162812,0.0008287856,0.0002445464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005926345,"about_ca_system_score_gemma":0.001289549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003461162,"about_ca_topic_score_gemma":0.004084798,"domain_scores_codex":[0.9994831,0.0001065048,0.00003311294,0.00007182163,0.0002392185,0.00006615926],"domain_scores_gemma":[0.9992908,0.0002954874,0.00008852093,0.00008959907,0.0001750095,0.00006053546],"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":[0.0002052782,0.0002500403,0.003816572,0.0002050411,0.00009770441,0.0001591048,0.0002543821,0.5892745,0.01702551,0.02314222,0.003159246,0.3624105],"study_design_scores_gemma":[0.0000717021,0.00013907,0.0004847355,0.00001043763,0.0000249938,0.00008128059,0.00003427382,0.9895563,0.003018494,0.003848332,0.002715557,0.00001482371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1026229,0.0005922118,0.8852281,0.000277787,0.0001543416,0.0001697592,0.00006721004,0.001214337,0.009673407],"genre_scores_gemma":[0.5889446,0.0003630886,0.4051394,0.0003639414,0.00007435009,0.0002374334,0.0001722993,0.0001884824,0.00451637],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003461162,"threshold_uncertainty_score":0.006882012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.059521488459502,"score_gpt":0.3073717523949919,"score_spread":0.2478502639354899,"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."}}