{"id":"W4312681734","doi":"10.1109/tfuzz.2022.3226250","title":"Design of Distributed Rule-Based Models in the Presence of Large Data","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Fuzzy Systems","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Weighting; Data mining; Curse of dimensionality; Boosting (machine learning); Machine learning; Data modeling; Artificial intelligence; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.0007530998,0.00008251853,0.0001528866,0.00007922594,0.0001799654,0.00002827365,0.001911679,0.00002260813,0.000003597869],"category_scores_gemma":[0.000001703007,0.00006554784,0.00003743924,0.0008747947,0.0000286749,0.0002031978,0.00001193534,0.0001857089,0.000001291174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002382902,"about_ca_system_score_gemma":0.00007208175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001712793,"about_ca_topic_score_gemma":0.00001099626,"domain_scores_codex":[0.9984738,0.0003932416,0.0003176826,0.0002704603,0.0003820199,0.0001627791],"domain_scores_gemma":[0.9980847,0.0004137461,0.0001279035,0.00131019,0.00003786258,0.00002554929],"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":[0.00001166322,0.000302391,0.000002869851,0.00001833828,0.00000690017,0.000001647483,0.0001496746,0.994745,0.0005066305,0.003214366,0.0005753441,0.0004651991],"study_design_scores_gemma":[0.0002591877,0.00006532962,0.00001302966,0.00002113358,0.000007336756,0.000004881379,0.0001226198,0.9981347,0.0006072507,0.0004021276,0.0002977563,0.00006467771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001522111,0.00008864915,0.9964322,0.0003688598,0.0002213649,0.0005831852,0.0007083946,0.00003049169,0.0000446843],"genre_scores_gemma":[0.9984729,0.000006356448,0.001159481,0.00004191663,0.000008467554,0.0002690761,0.00001837265,0.000005126833,0.00001826545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9969508,"threshold_uncertainty_score":0.3552407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06823746302586862,"score_gpt":0.2744964670999681,"score_spread":0.2062590040740995,"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."}}