{"id":"W4401520901","doi":"10.1021/acs.iecr.4c01980","title":"Unsupervised Hybrid Models Integrating Deep Autoencoders and Process Controllers’ Models for Enhanced Process Monitoring and Fault Detection","year":2024,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sanofi (Canada); University of Waterloo","funders":"Mitacs; Sanofi","keywords":"Overfitting; Computer science; Fault detection and isolation; Process (computing); Benchmark (surveying); Mean squared error; Controller (irrigation); Artificial neural network; Artificial intelligence; Control theory (sociology); Control (management); Mathematics","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":[0.0006884178,0.0003166284,0.0003552985,0.0001910067,0.0001817655,0.000438201,0.0001737081,0.0003087382,0.000003718446],"category_scores_gemma":[0.0002659204,0.000324888,0.0000691137,0.000425359,0.00004991762,0.0004926206,0.00002911987,0.001068534,8.949029e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002209522,"about_ca_system_score_gemma":0.00008578512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002784912,"about_ca_topic_score_gemma":0.000002000175,"domain_scores_codex":[0.998019,0.00002381177,0.0003989085,0.0004994163,0.0004298539,0.0006290182],"domain_scores_gemma":[0.9990555,0.0003177752,0.00002212237,0.0001697236,0.0002043238,0.0002305322],"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":[0.00005364135,0.000004777829,0.000001180018,0.0009077754,0.00007832631,0.000004165698,0.0005468217,0.5557041,0.4324546,0.000008430484,0.00000577934,0.01023051],"study_design_scores_gemma":[0.0008602724,0.00002930233,2.315607e-7,0.0003420232,0.00001370027,0.00001746987,0.0008167537,0.6258623,0.3716161,0.0001894787,0.00005735502,0.0001950626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8975524,0.002432465,0.09650583,0.00004706658,0.0007063926,0.001102834,0.0000255091,0.001100062,0.0005274485],"genre_scores_gemma":[0.997945,0.0000695384,0.00004937225,8.581961e-7,0.0008735218,0.0008574109,0.000006105377,0.00009747388,0.0001007291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1003926,"threshold_uncertainty_score":0.9999203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04984744633983069,"score_gpt":0.3120013431250766,"score_spread":0.2621538967852459,"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."}}