{"id":"W1999994061","doi":"10.1016/j.asoc.2011.04.005","title":"Design of interval type-2 fuzzy models through optimal granularity allocation","year":2011,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":108,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Granularity; Fuzzy logic; Computer science; Interval (graph theory); Data mining; Mathematical optimization; Membership function; Fuzzy set; Defuzzification; Fuzzy classification; Type (biology); Fuzzy number; Process (computing); Mathematics; Artificial intelligence","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":[0.000600314,0.000164541,0.000292758,0.0000433476,0.0001169354,0.0000426812,0.0008593712,0.00009418818,0.00000173649],"category_scores_gemma":[0.00001328311,0.0001542152,0.00005888314,0.0002728508,0.00005757587,0.000261654,0.0002943271,0.0001435024,0.00002687108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002792339,"about_ca_system_score_gemma":0.00006053925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001179172,"about_ca_topic_score_gemma":7.520096e-7,"domain_scores_codex":[0.9985822,0.00008498584,0.000405688,0.0003883058,0.000244271,0.0002945315],"domain_scores_gemma":[0.9990209,0.0001207436,0.0002194679,0.0004620424,0.0001267071,0.00005011414],"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":[0.00006039733,0.0001332061,0.00005997002,0.00003960003,0.00005569922,0.000004783451,0.01037992,0.0776822,0.00308695,0.8881375,0.0001111588,0.02024864],"study_design_scores_gemma":[0.0005224534,0.0001274301,0.0001659707,0.00003243925,0.00001411691,0.0000102367,0.000166134,0.8224038,0.001914238,0.1743762,0.00001670605,0.0002502392],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007536143,0.0001050712,0.9666069,0.00002545081,0.0002627937,0.0002963309,2.585692e-7,0.0001990797,0.02496798],"genre_scores_gemma":[0.7101198,0.000001672915,0.2897114,0.0001054589,0.00003890534,0.000005601713,0.000001161277,0.000007860355,0.000008149032],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7447216,"threshold_uncertainty_score":0.6288716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06838382500961226,"score_gpt":0.2398426756685281,"score_spread":0.1714588506589159,"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."}}