{"id":"W1523488457","doi":"10.3182/20020721-6-es-1901.01365","title":"DETECTION AND DIAGNOSIS OF SYSTEM NONLINEARITIES USING HIGHER ORDER STATISTICS","year":2002,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Process (computing); Identification (biology); CUSUM; Work in process; Engineering; Computer science; Artificial neural network; Reliability engineering; Data mining; Industrial engineering; Machine learning; Operations management","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":[0.0008213752,0.0005857289,0.001017356,0.001113402,0.0003475969,0.0007909932,0.0003785793,0.0006985295,0.0006739477],"category_scores_gemma":[0.003693156,0.0002961936,0.0004226243,0.0005554371,0.000525002,0.0009889308,0.0005099273,0.001029853,0.0002345232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004307357,"about_ca_system_score_gemma":0.0006618633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002001752,"about_ca_topic_score_gemma":0.003288724,"domain_scores_codex":[0.9993969,0.0001220328,0.0000516189,0.00008250415,0.0002884204,0.00005846734],"domain_scores_gemma":[0.996014,0.002912566,0.0003424325,0.0002881061,0.0003742709,0.0000686198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001288743,0.0003770957,0.01734393,0.0003290794,0.0002805765,0.000665277,0.0003627614,0.3133681,0.1450214,0.02809112,0.001935132,0.4909368],"study_design_scores_gemma":[0.00001467964,0.00008482699,0.004249857,0.00000645769,0.00002451887,0.0001581584,0.00001459736,0.9747118,0.0133199,0.007014277,0.0003838406,0.00001696951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07236339,0.0004550364,0.9256282,0.0001753795,0.00004865944,0.0000193775,0.00005651542,0.0005085394,0.0007447443],"genre_scores_gemma":[0.8539586,0.0004971914,0.143375,0.00008038432,0.0001075827,0.00003347458,0.0001701898,0.00004318399,0.001734335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002001752,"threshold_uncertainty_score":0.004343927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129867386279851,"score_gpt":0.2026033342159053,"score_spread":0.1896165955879202,"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."}}