{"id":"W2135812044","doi":"10.1002/cjce.21795","title":"Fault detection and diagnosis for distillation column using two‐tier model","year":2013,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distillation; Fractionating column; Fault detection and isolation; Nonlinear system; Fault (geology); Process (computing); Stripping (fiber); Linear model; Computer science; Engineering; Chemistry; Chromatography; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003887168,0.0007118013,0.0007228719,0.0004378878,0.0003634366,0.0006912632,0.0007517465,0.0006270966,0.001345852],"category_scores_gemma":[0.001011725,0.000350731,0.0006183768,0.0001870292,0.0003856285,0.0006909295,0.0005429726,0.0006052009,0.0002601681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001180059,"about_ca_system_score_gemma":0.001167304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02089736,"about_ca_topic_score_gemma":0.01681477,"domain_scores_codex":[0.9995648,0.00008368051,0.00002287288,0.000120889,0.0001526231,0.00005507311],"domain_scores_gemma":[0.9994331,0.000199895,0.00008929269,0.00005441082,0.0001966932,0.0000266709],"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":[0.0003051776,0.0001082106,0.004155412,0.00008189763,0.00006780357,0.0001315711,0.00008401875,0.9228669,0.02299848,0.002726955,0.0005131371,0.04596044],"study_design_scores_gemma":[0.000004678136,0.00002089224,0.000232173,0.000001060216,0.000003697736,0.000008691442,0.000002457435,0.998183,0.001268117,0.0002049865,0.00006655237,0.000003735559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07792,0.0001340476,0.9189381,0.0001286372,0.00002239522,0.00005698441,0.00008668889,0.001256039,0.001457161],"genre_scores_gemma":[0.9629088,0.00004638602,0.03564215,0.00003330602,0.000005682475,0.00003240546,0.00006591438,0.00001863073,0.001246715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02089736,"threshold_uncertainty_score":0.04155147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00925473925855949,"score_gpt":0.1905942057914352,"score_spread":0.1813394665328757,"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."}}