{"id":"W4407598381","doi":"10.1016/j.swevo.2024.101839","title":"Evolutionary algorithm based on multi-probability distribution model for stochastic optimization","year":2025,"lang":"en","type":"article","venue":"Swarm and Evolutionary Computation","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Computer science; Estimation of distribution algorithm; Algorithm; Evolutionary algorithm; Stochastic optimization; Probability distribution; Mathematical optimization; Artificial intelligence; Mathematics; Statistics","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":[0.001155058,0.0006865037,0.001483667,0.0007610549,0.0005832484,0.001145324,0.001550634,0.001434981,0.00156635],"category_scores_gemma":[0.00317373,0.0004883633,0.001253674,0.001354093,0.0008625527,0.001843032,0.0009534854,0.001859009,0.0002578657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001090939,"about_ca_system_score_gemma":0.0009601461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004852188,"about_ca_topic_score_gemma":0.002494944,"domain_scores_codex":[0.9994193,0.0002530104,0.00002345425,0.00007937908,0.0001839379,0.00004086069],"domain_scores_gemma":[0.9991785,0.0005578071,0.00005689179,0.00004345167,0.0001349137,0.00002839067],"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":[0.00001346208,0.0000210751,0.0002231996,0.00004127816,0.00004450295,0.00003936814,0.00002864407,0.9255509,0.0005511978,0.06063717,0.0005000145,0.01234912],"study_design_scores_gemma":[0.000002573326,0.000005002567,0.00003016879,0.000002118489,0.000003142686,0.00000768948,0.000001409074,0.995363,0.00003639613,0.004355084,0.000191391,0.00000206715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004584654,0.0004000748,0.9925324,0.0001647631,0.00007005281,0.00001666641,0.00001318842,0.0000399731,0.002178251],"genre_scores_gemma":[0.5850593,0.00188635,0.3994968,0.0002164558,0.0002438152,0.0003320069,0.0001864114,0.0001538462,0.0124249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004852188,"threshold_uncertainty_score":0.009647846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0294235800429321,"score_gpt":0.2983921817003596,"score_spread":0.2689686016574275,"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."}}