{"id":"W2008164953","doi":"10.1109/cec.2014.6900298","title":"Improved differential evolution with adaptive opposition strategy","year":2014,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Differential evolution; Opposition (politics); Benchmark (surveying); Computer science; Mathematical optimization; Algorithm; Artificial intelligence; 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":[0.0005337516,0.0004376215,0.0008549328,0.000489476,0.0002140904,0.0005024591,0.001003704,0.0006049604,0.001006758],"category_scores_gemma":[0.001144538,0.0002021215,0.0005287708,0.0004887883,0.0003982725,0.0004675909,0.0008227454,0.000588898,0.0002080899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003363799,"about_ca_system_score_gemma":0.0003103293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007391847,"about_ca_topic_score_gemma":0.000686865,"domain_scores_codex":[0.9996697,0.00008604615,0.00001418847,0.00004099451,0.0001579674,0.00003108187],"domain_scores_gemma":[0.9997311,0.000121395,0.00003097229,0.00002785907,0.00007305362,0.00001554479],"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":[0.00009343079,0.00007720411,0.0009008949,0.0001115107,0.00007794287,0.0002106704,0.00009863243,0.795058,0.01407599,0.0314017,0.001470295,0.1564237],"study_design_scores_gemma":[0.00001472048,0.00003677592,0.0001043676,0.000003542057,0.000006384453,0.00004983474,0.000003596536,0.9953848,0.0008674347,0.002189459,0.001333673,0.000005415155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02994815,0.0004157101,0.9615046,0.0001171591,0.00007761301,0.0000448187,0.00002561811,0.00018787,0.007678338],"genre_scores_gemma":[0.7158439,0.0002909114,0.2770114,0.0001784945,0.00004213087,0.0001659328,0.00009192142,0.00006267659,0.006312677],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001006758,"threshold_uncertainty_score":0.003367901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642090508593768,"score_gpt":0.2446009214964647,"score_spread":0.228180016410527,"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."}}