{"id":"W2120593887","doi":"10.1109/nafips.2006.365849","title":"Validation of Hybrid MinMax FuzzyNeuro Systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Fuzzy inference system; Computer science; Generalization; Minimax; Hybrid system; Perspective (graphical); Inference; Value (mathematics); Fuzzy logic; Artificial intelligence; Fuzzy control system; Machine learning; Mathematical optimization; Mathematics; Adaptive neuro fuzzy inference system","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":[0.0001916724,0.00007601342,0.0001510449,0.00005416441,0.00003160407,0.00007397384,0.0004054859,0.00001794577,0.000002693958],"category_scores_gemma":[0.000009666958,0.000059584,0.00004915877,0.0001390579,0.00001559655,0.0002087039,0.00005263514,0.00002937262,0.00005371659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001334663,"about_ca_system_score_gemma":0.00002219455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005498353,"about_ca_topic_score_gemma":0.000001388387,"domain_scores_codex":[0.9990868,0.00006380076,0.0002798059,0.0001937585,0.0002346051,0.0001412107],"domain_scores_gemma":[0.9993679,0.00005715572,0.000110483,0.0003590697,0.00007823161,0.00002715178],"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":[0.000003854292,0.00007678028,0.001498064,0.00004889518,0.00001057204,0.00001915819,0.00002831789,0.003197213,0.009567549,0.9707056,0.01340698,0.001436973],"study_design_scores_gemma":[0.005900014,0.00121786,0.01604883,0.0002343688,0.00007549785,0.000833404,0.0002704301,0.4629877,0.2925571,0.1578019,0.05976205,0.002310835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1577741,0.000412234,0.4626593,0.0003320311,0.001277996,0.000329959,0.000003309339,0.0002661011,0.376945],"genre_scores_gemma":[0.996506,0.000001053435,0.000879402,0.0000361193,0.000102157,0.0000114715,0.000002240383,0.000003386904,0.002458223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8387319,"threshold_uncertainty_score":0.2429765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00823871531520738,"score_gpt":0.1881089010199109,"score_spread":0.1798701857047036,"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."}}