{"id":"W4399728550","doi":"10.1109/tim.2024.3415233","title":"Data-Driven Plant–Model Mismatch Detection for Closed-Loop LPV System Based on Instrumental Variable Using Sum-of-Norms Regularization","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China","keywords":"Instrumental variable; Regularization (linguistics); Closed loop; Control theory (sociology); Variable (mathematics); Data modeling; Computer science; Mathematics; Control engineering; Artificial intelligence; Engineering; Econometrics; Control (management); Mathematical analysis","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":[0.001401241,0.001100877,0.000933128,0.0004591827,0.000363066,0.0009469945,0.0009202957,0.0009825381,0.0009734951],"category_scores_gemma":[0.003170147,0.0004020915,0.0006999269,0.0003823185,0.0007557566,0.0009797632,0.001259529,0.001609864,0.0002375388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005732813,"about_ca_system_score_gemma":0.0009370053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002101076,"about_ca_topic_score_gemma":0.00149124,"domain_scores_codex":[0.9992943,0.0002318729,0.00004290952,0.0001457894,0.0002372824,0.00004787044],"domain_scores_gemma":[0.998881,0.0006575306,0.0001639472,0.00007369529,0.0001930979,0.00003058239],"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":[0.0002209064,0.0001024283,0.001094208,0.0002474535,0.0001145468,0.0001268724,0.000219858,0.8319778,0.02330998,0.01864021,0.0009959101,0.1229499],"study_design_scores_gemma":[0.000001797284,0.0000164592,0.00005610489,0.000003233547,0.00000233636,0.000007151204,0.000003228524,0.9976535,0.001312703,0.0007730659,0.0001651457,0.000005199214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00462587,0.00005316563,0.9947845,0.00003284889,0.00001044775,0.00001076529,0.000007403428,0.0001532097,0.0003218021],"genre_scores_gemma":[0.7102944,0.0002177519,0.2862579,0.0001076991,0.00004804305,0.0002213954,0.0001685006,0.0001807211,0.002503489],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002101076,"threshold_uncertainty_score":0.007410586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04581292589154312,"score_gpt":0.2471955791582338,"score_spread":0.2013826532666907,"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."}}