{"id":"W2315656662","doi":"10.1021/ie503641c","title":"Multi-input–Multi-output (MIMO) Control System Performance Monitoring Based on Dissimilarity Analysis","year":2014,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; Shanghai Municipal Education Commission; National Natural Science Foundation of China; Ministry of Science and Technology of the People's Republic of China; University of Alberta","keywords":"Covariance; Computer science; Eigenvalues and eigenvectors; MIMO; Fractionating column; Orientation (vector space); Control theory (sociology); Distillation; Column (typography); Control (management); Covariance matrix; Algorithm; Mathematics; Artificial intelligence; Statistics; Chemistry; Chromatography","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":[0.0006667585,0.0006981266,0.0006856014,0.0009313227,0.0003179614,0.0007003252,0.0004801437,0.0004204732,0.000721863],"category_scores_gemma":[0.002865161,0.0002012752,0.0003549564,0.0006417472,0.0003855566,0.001049991,0.0006905089,0.0005106038,0.0001706009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003444494,"about_ca_system_score_gemma":0.0002108939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005190799,"about_ca_topic_score_gemma":0.000575718,"domain_scores_codex":[0.9989773,0.0001804672,0.00006828232,0.0002235496,0.0005043595,0.00004608915],"domain_scores_gemma":[0.9985678,0.000502746,0.0003341698,0.0001531117,0.000376941,0.00006519441],"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":[0.0013125,0.0004071005,0.01479873,0.0004990921,0.0002963914,0.0003629456,0.000388779,0.1986733,0.2494621,0.009371026,0.001264798,0.5231631],"study_design_scores_gemma":[0.00001905879,0.0003708021,0.0080355,0.000009707782,0.0000287104,0.0002625248,0.00004244368,0.9526381,0.03556957,0.00186808,0.001094083,0.00006143739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0495813,0.0001689778,0.9487201,0.00005830408,0.00004045193,0.00003592822,0.00004485942,0.0003066246,0.001043499],"genre_scores_gemma":[0.8587345,0.0001105716,0.1401399,0.00003844492,0.00005597101,0.00006041385,0.0001044675,0.00004474104,0.0007109842],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009313227,"threshold_uncertainty_score":0.003526151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05857426984325675,"score_gpt":0.2939933301876975,"score_spread":0.2354190603444407,"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."}}