{"id":"W2166637398","doi":"10.1109/grc.2007.118","title":"Type-2 Fuzzy Logic: Theory and Applications","year":2007,"lang":"en","type":"article","venue":"2007 IEEE International Conference on Granular Computing (GRC 2007)","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Membership function; Fuzzy set; Fuzzy classification; Defuzzification; Fuzzy set operations; Type-2 fuzzy sets and systems; Fuzzy number; Fuzzy logic; Mathematics; Fuzzy mathematics; Type (biology); Artificial intelligence; Computer science; Data mining","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":[0.001258678,0.0008504989,0.001238343,0.001569699,0.0009784343,0.003104179,0.001385479,0.002008919,0.004245986],"category_scores_gemma":[0.003052198,0.000402081,0.001047943,0.00348942,0.001738745,0.002662432,0.001205181,0.002257342,0.001211614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001799423,"about_ca_system_score_gemma":0.001273735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002462141,"about_ca_topic_score_gemma":0.0009874117,"domain_scores_codex":[0.9987682,0.0002577116,0.000112619,0.0002022765,0.0005895027,0.00006966163],"domain_scores_gemma":[0.9989254,0.0004891402,0.0001216062,0.000091469,0.0003293306,0.00004305676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008429884,0.00006298638,0.0009707471,0.001088323,0.00009990325,0.0006192397,0.0003849577,0.05805802,0.002958533,0.6647907,0.01684678,0.2540355],"study_design_scores_gemma":[0.0000231717,0.00004731853,0.0003354044,0.0003519441,0.00003728355,0.000572652,0.0001379251,0.1740119,0.001255928,0.7506015,0.07256745,0.00005750682],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004573791,0.03720544,0.9100339,0.002672767,0.0009853296,0.000107905,0.0003131421,0.0003964423,0.04371116],"genre_scores_gemma":[0.4242437,0.0689441,0.4770578,0.002042817,0.003204869,0.0004391655,0.0007422599,0.0001780875,0.02314707],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004245986,"threshold_uncertainty_score":0.01420426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03501395842559664,"score_gpt":0.2980051901315944,"score_spread":0.2629912317059978,"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."}}