{"id":"W4410640023","doi":"10.1109/lcsys.2025.3573124","title":"On Regular Regressors in Adaptive Control","year":2025,"lang":"en","type":"article","venue":"IEEE Control Systems Letters","topic":"Control Systems and Identification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control (management); Computer science; Statistics; Mathematics; Econometrics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00172268,0.0007432083,0.0007603561,0.0007407534,0.00046086,0.001004785,0.0005820484,0.001165419,0.002889584],"category_scores_gemma":[0.004747391,0.0003338674,0.0006134833,0.0006193535,0.003418184,0.002423468,0.001453515,0.002534663,0.0005097439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009069813,"about_ca_system_score_gemma":0.0004324864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001436371,"about_ca_topic_score_gemma":0.0008389502,"domain_scores_codex":[0.9991136,0.0003293113,0.00003990811,0.0001994015,0.0002329555,0.0000847344],"domain_scores_gemma":[0.9976004,0.001699043,0.000181037,0.0001806827,0.0002386466,0.000100286],"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":[0.00003168463,0.00001231592,0.0002368774,0.00007282264,0.00001665939,0.00006267284,0.0000941636,0.0481088,0.001480022,0.9350793,0.0009904281,0.01381429],"study_design_scores_gemma":[0.00001367929,0.00006444085,0.0002336798,0.00004314278,0.000008990711,0.00004969996,0.00003110885,0.2003865,0.0005808018,0.7913831,0.007183945,0.00002095181],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01971644,0.005345019,0.947839,0.002350537,0.0003147028,0.00002271044,0.00008015517,0.0001262995,0.02420522],"genre_scores_gemma":[0.857865,0.01103472,0.1025462,0.001218129,0.002110519,0.0001505058,0.0002033607,0.0002124281,0.02465907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002889584,"threshold_uncertainty_score":0.009666562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004991701848899808,"score_gpt":0.188298961031589,"score_spread":0.1833072591826892,"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."}}