{"id":"W2607855551","doi":"10.1109/tac.2017.2696740","title":"Iterative Residual Generator for Fault Detection With Linear Time-Invariant State–Space Models","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Alberta Innovates - Technology Futures","keywords":"Control theory (sociology); Residual; Fault detection and isolation; Kalman filter; Mathematics; False alarm; Finite impulse response; Algorithm; Computer science; Actuator; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002194344,0.0003173411,0.0004256653,0.0001541483,0.0006873552,0.0002673517,0.0001929726,0.0001326892,0.00004547636],"category_scores_gemma":[0.00001269667,0.0002716663,0.0001394539,0.00007453201,0.00005100774,0.0004221209,5.575101e-7,0.0001884074,0.00009010367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001374684,"about_ca_system_score_gemma":0.00004694658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006360414,"about_ca_topic_score_gemma":0.0004106336,"domain_scores_codex":[0.9986467,0.00006992853,0.0003740866,0.0003004276,0.0002585583,0.0003502591],"domain_scores_gemma":[0.9988649,0.0001512422,0.0001314193,0.0005798136,0.0001324258,0.0001401252],"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":[0.0002671306,0.00006010364,3.954283e-7,0.00007725588,0.0004432519,0.000006494391,0.0004532044,0.9150544,0.05402117,0.00001320068,0.0001027732,0.02950059],"study_design_scores_gemma":[0.004401593,0.0003535688,0.00001416596,0.00007296957,0.0001234925,0.00002139532,0.00004338925,0.9430854,0.05124607,0.00005053576,0.0002786118,0.0003087962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05737104,0.00002604472,0.9391832,0.0001846769,0.0006886308,0.00129949,0.0001887751,0.0007857054,0.0002724938],"genre_scores_gemma":[0.9963412,0.000005188442,0.001332502,0.0000627168,0.0001461278,0.0008931735,0.000001857677,0.00007934568,0.001137879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9389701,"threshold_uncertainty_score":0.9999735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048896700342084,"score_gpt":0.2253099344947511,"score_spread":0.2148209674913303,"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."}}