{"id":"W2102917763","doi":"10.1109/icit.2004.1490729","title":"Design and implementation of a stable fuzzy model reference learning controller applied to a rigid-link manipulator","year":2005,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Control theory (sociology); Robustness (evolution); Computer science; Link (geometry); Fuzzy logic; Control engineering; Fuzzy control system; Trajectory; Controller (irrigation); Stability (learning theory); Artificial intelligence; Engineering; Control (management); Machine learning","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":[0.0004350351,0.0001164196,0.0002336098,0.0000713454,0.00006948361,0.0000803484,0.0002626568,0.00004376801,0.000008493686],"category_scores_gemma":[0.000007236686,0.0000946783,0.00001854506,0.0001631227,0.00001068595,0.0002219506,0.0001021875,0.0000699404,0.00002634286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003413427,"about_ca_system_score_gemma":0.00006206717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001131963,"about_ca_topic_score_gemma":0.00002720207,"domain_scores_codex":[0.9988853,0.00005279523,0.0002993117,0.0003072767,0.0002145669,0.0002407534],"domain_scores_gemma":[0.9994641,0.0000659128,0.0001005749,0.0001853749,0.00008714024,0.00009691787],"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":[0.00007682791,0.00002529507,0.000183196,0.00001719585,0.00003299063,6.543424e-7,0.00184077,0.2806004,0.03195677,0.6237236,0.00045066,0.06109162],"study_design_scores_gemma":[0.001974553,0.0001726397,0.0002699191,0.000008425553,0.0000101231,0.000002860662,0.0002807785,0.9833138,0.002539265,0.0104732,0.0007437793,0.0002106786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009852228,0.00005239765,0.9750171,0.0005216692,0.0000151505,0.00058866,6.251845e-7,0.00008835823,0.0138638],"genre_scores_gemma":[0.8586127,0.000003508808,0.1403104,0.0002885865,0.00002562916,0.00007436471,6.562038e-7,0.000005092339,0.0006791186],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8487605,"threshold_uncertainty_score":0.3860869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03283838297322717,"score_gpt":0.2648240750075518,"score_spread":0.2319856920343247,"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."}}