{"id":"W1524160437","doi":"10.1007/978-3-642-01085-9_17","title":"PSO_Bounds: A New Hybridization Technique of PSO and EDAs","year":2009,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"EDAS; Estimation of distribution algorithm; Particle swarm optimization; Benchmark (surveying); Mathematical optimization; Computer science; Population; Artificial intelligence; Mathematics; Geography; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005608844,0.0003025612,0.0005322031,0.0006202056,0.00008750417,0.00007081276,0.000698616,0.0001365098,0.00003928617],"category_scores_gemma":[0.0004588816,0.0003117953,0.00006677953,0.000303624,0.0004056011,0.0002096616,0.0005150171,0.0003420045,0.00002004199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001498043,"about_ca_system_score_gemma":0.0004336555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001551847,"about_ca_topic_score_gemma":0.000009087121,"domain_scores_codex":[0.9975138,0.00005567883,0.0008290147,0.0006306025,0.0007573874,0.0002135449],"domain_scores_gemma":[0.9975398,0.0007854212,0.0003646591,0.000366112,0.0008532425,0.00009081808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007800328,0.00002721002,0.000005890672,0.0001129854,0.00007612095,0.00002991636,0.000582438,0.06368554,0.000001492486,0.7626837,0.001181378,0.1716055],"study_design_scores_gemma":[0.00008911621,0.00014843,0.00002732406,0.0004994242,0.00001112572,0.00004762954,0.00002295997,0.1613378,0.0001164305,0.8333335,0.004055774,0.0003104963],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[8.622176e-7,0.004454014,0.9649562,0.0004950113,0.0002022918,0.0005289142,0.000008523651,0.00005639176,0.0292978],"genre_scores_gemma":[0.002825783,0.00617378,0.9340852,0.0002018558,0.0001393915,0.00003086579,0.00002876273,0.00003504284,0.05647929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.171295,"threshold_uncertainty_score":0.9999334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1090581124548539,"score_gpt":0.3856699672446664,"score_spread":0.2766118547898125,"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."}}