{"id":"W2901962248","doi":"10.1002/cjce.23401","title":"Operating performance assessment and non‐optimal cause identification for chemical process","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Principal component analysis; Variance (accounting); Identification (biology); Process (computing); Data mining; Similarity (geometry); Feature (linguistics); Computer science; Plot (graphics); Pattern recognition (psychology); Artificial intelligence; Machine learning; Mathematics; Statistics","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":[0.001717373,0.00100468,0.0006668462,0.002078788,0.0005397262,0.0009533614,0.0005652552,0.0004682555,0.0007606441],"category_scores_gemma":[0.0038229,0.0003021551,0.0007756799,0.0007490027,0.0005261636,0.001184419,0.0008638281,0.0007192759,0.0001267928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006945927,"about_ca_system_score_gemma":0.001334323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004469012,"about_ca_topic_score_gemma":0.00387774,"domain_scores_codex":[0.9982461,0.0004858962,0.00009176752,0.0002862452,0.0007927138,0.0000974297],"domain_scores_gemma":[0.9985448,0.0006093157,0.0002604635,0.00009285029,0.0004514181,0.00004122439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003254009,0.000246873,0.01510283,0.0002369162,0.0001780662,0.0002199075,0.000314245,0.5932963,0.02555804,0.007988564,0.0007133274,0.3558195],"study_design_scores_gemma":[0.00000371397,0.0000603828,0.002606093,0.000003218854,0.00001386162,0.00002081034,0.00002425733,0.9919032,0.003476244,0.001667881,0.0002071124,0.00001322998],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08432774,0.0001836705,0.9140854,0.00006382123,0.00001437926,0.0000550631,0.00002605466,0.0002315685,0.001012246],"genre_scores_gemma":[0.9184995,0.00009283183,0.08032838,0.0000115832,0.00001337234,0.00004811066,0.00006471849,0.00002777552,0.0009136903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004469012,"threshold_uncertainty_score":0.009082437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0076436106769416,"score_gpt":0.2290832563342409,"score_spread":0.2214396456572993,"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."}}