{"id":"W4388294700","doi":"10.1016/j.eswa.2023.122335","title":"Lévy Arithmetic Algorithm: An enhanced metaheuristic algorithm and its application to engineering optimization","year":2023,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Algorithm; Metaheuristic; Mathematics; Benchmark (surveying); Mathematical optimization; Computer science; Arithmetic; Optimization problem","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006736022,0.0003515654,0.0004015822,0.0007526096,0.0003895195,0.0004781598,0.0009794321,0.0001212185,0.000009774766],"category_scores_gemma":[0.00009742689,0.0003336742,0.00003652248,0.003601702,0.00003664302,0.0006669726,0.0002589017,0.0001817364,0.0002902669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198655,"about_ca_system_score_gemma":0.0001157563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006029478,"about_ca_topic_score_gemma":0.000001292349,"domain_scores_codex":[0.9967405,0.000135971,0.0005681721,0.001155317,0.0008087653,0.0005913064],"domain_scores_gemma":[0.9971664,0.0002175259,0.0001682747,0.00121524,0.0006242856,0.000608251],"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":[0.000004333082,0.0001346206,0.000002337605,0.00007608162,0.00006937142,0.000007488609,0.0008447584,0.814134,0.00184245,0.01419055,0.000244394,0.1684496],"study_design_scores_gemma":[0.0003245218,0.0001027658,0.00004983155,0.00003076869,0.00001236015,0.00003703095,0.0001087388,0.9896351,0.0008168512,0.00003405585,0.008446431,0.000401592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002754605,0.0004872956,0.994495,0.0005349705,0.0001590305,0.003001424,0.00003442356,0.001149548,0.0001107475],"genre_scores_gemma":[0.01023982,0.0002532918,0.9766819,0.000108187,0.0003201636,0.01140417,0.0001958754,0.00009020493,0.0007064025],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.175501,"threshold_uncertainty_score":0.9999115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01527639471665008,"score_gpt":0.2814307661597071,"score_spread":0.266154371443057,"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."}}