{"id":"W3104233578","doi":"10.1002/cjce.23923","title":"Dynamic process monitoring using dynamic latent‐variable and canonical correlation analysis model","year":2020,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Jiangnan University; National Natural Science Foundation of China","keywords":"Linear subspace; Canonical correlation; Control theory (sociology); Process (computing); Latent variable; Computer science; Canonical form; Mathematics; Algorithm; Mathematical optimization; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001199931,0.0001269015,0.0002486859,0.0001352122,0.00005335132,0.00007008656,0.0001427612,0.00008973318,0.000004587104],"category_scores_gemma":[0.00006587311,0.0001111748,0.00007890562,0.0004569718,0.00001897428,0.0001232096,0.000005721005,0.000387989,6.762555e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002779361,"about_ca_system_score_gemma":0.0001385037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002044203,"about_ca_topic_score_gemma":0.0000833002,"domain_scores_codex":[0.9992374,0.000007549434,0.0003060009,0.00008371773,0.0001385207,0.0002267978],"domain_scores_gemma":[0.9993711,0.00002849904,0.00005493791,0.00007379974,0.00005773813,0.0004139546],"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":[0.000003789499,6.141962e-7,0.0002506493,0.00003023206,0.0001442467,0.000005269695,0.0002350882,0.9461629,0.05303281,0.0000134789,0.000001530585,0.0001193772],"study_design_scores_gemma":[0.000182282,0.000006342073,0.00008584802,0.00004168904,0.0001992947,0.00004616109,0.00002083799,0.9981417,0.001125807,0.00001732648,0.00001720886,0.0001154729],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9189252,0.0008326193,0.07977992,0.0001293562,0.0002008614,0.00005753958,0.00000541001,0.00004073201,0.00002835499],"genre_scores_gemma":[0.9991158,0.000003773691,0.0007668556,0.00001523838,0.00006609515,0.000001602291,0.000001014795,0.00002544219,0.000004236921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08019054,"threshold_uncertainty_score":0.4533578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007872039137300701,"score_gpt":0.2008437757585209,"score_spread":0.1929717366212202,"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."}}