{"id":"W1964465571","doi":"10.1016/j.asoc.2014.04.018","title":"Improved global-best particle swarm optimization algorithm with mixed-attribute data classification capability","year":2014,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Particle swarm optimization; Computer science; Multi-swarm optimization; Algorithm; Metaheuristic; Data mining; Mathematical optimization; Artificial intelligence; Pattern recognition (psychology); Mathematics","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":[0.002163681,0.0002900503,0.0003428514,0.0000639727,0.0004655315,0.0005591185,0.002224306,0.0001132113,0.00001219222],"category_scores_gemma":[0.0004076403,0.0002702035,0.0000334447,0.001318865,0.0001590972,0.0005167646,0.00124113,0.0002604645,0.00007050684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001652593,"about_ca_system_score_gemma":0.0001953311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005768552,"about_ca_topic_score_gemma":0.00000934937,"domain_scores_codex":[0.9964416,0.0002498901,0.0005953314,0.001310625,0.0007324337,0.0006701233],"domain_scores_gemma":[0.9960034,0.0004600606,0.0003218224,0.002489531,0.0004387004,0.0002864258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001609718,0.0003329671,0.001017194,0.00004753521,0.00005713345,0.000002660586,0.0001685365,0.4537178,0.0001619798,0.01435442,0.0002759126,0.5298477],"study_design_scores_gemma":[0.0007896341,0.00007355546,0.0009896905,0.00001317685,0.00001960173,0.00001075901,0.00006057796,0.9966984,0.0004031207,0.0002694488,0.0003553792,0.0003166987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001745444,0.0000224389,0.995692,0.0005145491,0.0002259981,0.000595206,0.0000233846,0.0004727626,0.0007082414],"genre_scores_gemma":[0.3738509,0.000002986048,0.6257159,0.0001201343,0.0000975999,0.00001643163,0.0001595628,0.00001769746,0.00001875177],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5429806,"threshold_uncertainty_score":0.999975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0402902922792972,"score_gpt":0.2917649241538687,"score_spread":0.2514746318745715,"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."}}