{"id":"W2036552982","doi":"10.1109/cec.2010.5585953","title":"Evolving ARTMAP neural networks using Multi-Objective Particle Swarm Optimization","year":2010,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Particle swarm optimization; Artificial neural network; Computer science; Artificial intelligence; Machine learning; Fuzzy logic","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":[0.001118841,0.0007365191,0.0007427633,0.0007432417,0.0003506075,0.001020222,0.001083613,0.001304608,0.001512022],"category_scores_gemma":[0.003183853,0.0004188548,0.0005908988,0.000514019,0.0005606132,0.001016921,0.0006746552,0.0007435547,0.0003100271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006712276,"about_ca_system_score_gemma":0.0005196265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002853781,"about_ca_topic_score_gemma":0.002794545,"domain_scores_codex":[0.9997563,0.00009530482,0.00001187278,0.00004135518,0.00007269954,0.0000224788],"domain_scores_gemma":[0.9991947,0.000498476,0.00007785371,0.00004999154,0.0001550583,0.00002391412],"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":[0.00002408632,0.00002635337,0.0003457005,0.00003028456,0.00002962272,0.00003906028,0.00004180446,0.9563883,0.0009083624,0.002925836,0.0003901049,0.03885042],"study_design_scores_gemma":[0.000002567111,0.000008613908,0.0000271057,0.000002433419,0.000002009851,0.000005494137,0.000003194845,0.9989752,0.0001816224,0.0006627062,0.0001274238,0.000001762733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03986219,0.0003551821,0.9548525,0.0001618546,0.00005380759,0.00007590838,0.00003125797,0.0003189818,0.004288322],"genre_scores_gemma":[0.5811788,0.0003127564,0.4129459,0.0002162318,0.00005141082,0.0003635659,0.0001189926,0.0000968349,0.004715485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002853781,"threshold_uncertainty_score":0.005917072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02264393466847631,"score_gpt":0.2671626394637635,"score_spread":0.2445187047952871,"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."}}