{"id":"W1604178182","doi":"10.1109/nafips.1999.781729","title":"On the robustness of fuzzy inference mechanism","year":2003,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Robustness (evolution); Fuzzy logic; Adaptive neuro fuzzy inference system; Fuzzy inference; Inference; Computer science; Artificial intelligence; Defuzzification; Parameterized complexity; Fuzzy number; Fuzzy classification; Fuzzy control system; Fuzzy set operations; Fuzzy set; Fuzzy inference system; Data mining; Machine learning; Mathematics; Algorithm","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":[0.01252663,0.001351972,0.001675972,0.001887826,0.0008092595,0.003626525,0.001949702,0.00305082,0.002026944],"category_scores_gemma":[0.0728687,0.0006340188,0.002034954,0.001085571,0.003695775,0.005105555,0.002057735,0.002063271,0.0005407337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726725,"about_ca_system_score_gemma":0.0006988837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001260482,"about_ca_topic_score_gemma":0.0002737754,"domain_scores_codex":[0.9926293,0.00295968,0.0005964898,0.001474642,0.00180318,0.0005368011],"domain_scores_gemma":[0.9590384,0.02986979,0.002934952,0.005242892,0.002505523,0.0004083834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005372342,0.00004903836,0.001027666,0.0002429017,0.0003353958,0.0004094598,0.000293189,0.8030739,0.01365463,0.1465665,0.0004443239,0.03336569],"study_design_scores_gemma":[0.00003192738,0.0001744349,0.0004856838,0.00005714488,0.00006866069,0.0001563977,0.00003774475,0.8842312,0.004677533,0.1094204,0.0006048128,0.00005405087],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07670904,0.001673943,0.9126659,0.0007755554,0.000105702,0.00007256392,0.00009569956,0.0004101839,0.007491392],"genre_scores_gemma":[0.9602094,0.0008029466,0.03713413,0.0001275698,0.0001638616,0.0001049641,0.00009425318,0.00010063,0.001262272],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01252663,"threshold_uncertainty_score":0.06624794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02082640986774291,"score_gpt":0.2187257267581924,"score_spread":0.1978993168904495,"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."}}