{"id":"W2169550434","doi":"10.1109/icsmc.1997.638103","title":"Hierarchical fuzzy controllers: fuzzy gain scheduling","year":2002,"lang":"en","type":"article","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Gain scheduling; Fuzzy logic; Fuzzy control system; Control theory (sociology); Computer science; Scheduling (production processes); Hierarchical control system; Control engineering; Control (management); Mathematics; Mathematical optimization; Engineering; 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":[0.00006165629,0.0001003065,0.0001205315,0.00005064712,0.00004818007,0.00002645028,0.00006323052,0.00007647589,0.0004918649],"category_scores_gemma":[0.00002530139,0.00009037937,0.00005579162,0.0001161231,0.00001766271,0.00008747616,0.000007512433,0.0001626901,0.0004989259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000303871,"about_ca_system_score_gemma":0.00000129428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001227449,"about_ca_topic_score_gemma":0.00000522854,"domain_scores_codex":[0.9993876,0.00001559735,0.0001600641,0.0001006651,0.0001149648,0.000221145],"domain_scores_gemma":[0.9997446,0.0000440622,0.000008417932,0.0001098117,0.00001797564,0.00007515808],"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":[0.00008006216,0.0001767948,0.0008319469,0.0001324627,0.0002425783,0.00008134291,0.001867638,0.5692979,0.1842423,0.0854049,0.01896013,0.138682],"study_design_scores_gemma":[0.001156056,0.0000374281,0.0002406508,0.00001986759,0.00001436451,0.000008905476,0.00005456734,0.981863,0.009588151,0.002577402,0.004147273,0.0002923872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3976867,0.000562435,0.01176894,0.0005907151,0.0005298788,0.0001991097,0.000003366227,0.0009716264,0.5876873],"genre_scores_gemma":[0.9970562,0.00004219265,0.001809375,0.0001440568,0.0003046173,0.000005719392,0.0000044464,0.00002059347,0.0006127654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5993695,"threshold_uncertainty_score":0.6412849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487298505343242,"score_gpt":0.2143360574617,"score_spread":0.1994630724082675,"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."}}