{"id":"W2051542317","doi":"10.5430/air.v1n2p149","title":"Fuzzy adaptive catfish particle swarm optimization","year":2012,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Council","keywords":"Catfish; Particle swarm optimization; Benchmark (surveying); Fuzzy logic; Inertia; Swarm intelligence; Multi-swarm optimization; Swarm behaviour; Mathematical optimization; Computer science; Artificial intelligence; Mathematics; Fish <Actinopterygii>; Biology; Physics; Fishery; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005855088,0.0001867413,0.0002136026,0.0004134781,0.0006102212,0.0005455503,0.001557371,0.00012411,0.0004040414],"category_scores_gemma":[0.001903909,0.0001805456,0.00007516125,0.003284232,0.0003725536,0.001535145,0.0007645665,0.000626208,0.002845183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002076332,"about_ca_system_score_gemma":0.0002649284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001695498,"about_ca_topic_score_gemma":0.0000134085,"domain_scores_codex":[0.9944419,0.0009488988,0.0005638857,0.0005862176,0.001860794,0.001598323],"domain_scores_gemma":[0.9960567,0.0009316,0.00007854676,0.0009832084,0.001287677,0.0006622471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003776963,0.0005887108,0.0002730034,0.00001204511,0.00002764399,0.00001472131,0.00263187,0.09693044,0.0004336039,0.7367186,0.0009123731,0.1614192],"study_design_scores_gemma":[0.00003050341,0.0001475468,0.00006519952,0.00001174071,0.000003117517,0.000009606389,0.0006991589,0.9244534,0.05415109,0.01961513,0.0005890455,0.0002244821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002070002,0.0002806129,0.986136,0.001715882,0.0004645699,0.0005268443,0.000002713251,0.0001809029,0.008622503],"genre_scores_gemma":[0.8055713,0.0001275164,0.1930855,0.00007765488,0.0003722036,0.0001117386,0.000005214244,0.00002593549,0.0006229524],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8275229,"threshold_uncertainty_score":0.9979312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2825149335201376,"score_gpt":0.4290115289024241,"score_spread":0.1464965953822865,"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."}}