{"id":"W4323342267","doi":"10.5267/j.ijiec.2023.1.002","title":"Hybrid algorithm proposal for optimizing benchmarking problems: Salp swarm algorithm enhanced by arithmetic optimization algorithm","year":2023,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Algorithm; Benchmark (surveying); Benchmarking; Context (archaeology); Swarm behaviour; Optimization algorithm; Computer science; Swarm intelligence; Metaheuristic; Mathematics; Particle swarm optimization; Mathematical optimization; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001152959,0.0007410934,0.0008824356,0.001176554,0.0003876098,0.0008994868,0.001379935,0.0007922873,0.002665661],"category_scores_gemma":[0.001373198,0.0002506179,0.0007387621,0.001307803,0.0004826134,0.0007960715,0.0009854203,0.0008358773,0.0005465634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003853099,"about_ca_system_score_gemma":0.0009466129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001889272,"about_ca_topic_score_gemma":0.001358241,"domain_scores_codex":[0.9994236,0.0001769777,0.00003111761,0.00007152167,0.0002485292,0.00004830988],"domain_scores_gemma":[0.9996265,0.0001271307,0.0000301084,0.00004223853,0.0001524709,0.00002147656],"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":[0.0001229623,0.00008673278,0.00126864,0.0001905177,0.0001285387,0.00009806522,0.00009659855,0.7241243,0.00741989,0.02468404,0.003224718,0.2385551],"study_design_scores_gemma":[0.00001954077,0.00005995178,0.0001558645,0.000007582053,0.00001180069,0.00003043382,0.00001141786,0.9937205,0.001319105,0.002215185,0.002441564,0.000006958684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01940162,0.0004163874,0.9726131,0.0001581212,0.0001202601,0.00007940218,0.00004450246,0.00060854,0.00655816],"genre_scores_gemma":[0.4021631,0.0004916599,0.5909442,0.0001707017,0.0001190703,0.000434081,0.000355582,0.0001678542,0.00515378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002665661,"threshold_uncertainty_score":0.00891757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02614145670597141,"score_gpt":0.2875177971073566,"score_spread":0.2613763404013852,"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."}}