{"id":"W3114138993","doi":"10.1002/cjce.24016","title":"Quality relevant fault detection of batch process via statistical pattern and regression coefficient","year":2020,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Principal component regression; Linear regression; Fault detection and isolation; Principal component analysis; Computer science; Regression analysis; Regression; Batch processing; Statistics; Soft sensor; Data mining; Partial least squares regression; Pattern recognition (psychology); Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007926112,0.0007306221,0.0006725804,0.001669733,0.0002763165,0.0006210184,0.0006612104,0.0004684345,0.0005578657],"category_scores_gemma":[0.004009676,0.000278085,0.0004999423,0.001485679,0.0003768925,0.000835345,0.0004081731,0.0006665111,0.0002165612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005110903,"about_ca_system_score_gemma":0.0007312848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004684014,"about_ca_topic_score_gemma":0.002946146,"domain_scores_codex":[0.9989834,0.0001471771,0.00005776248,0.0002514092,0.0004866736,0.00007352804],"domain_scores_gemma":[0.998064,0.0006309095,0.0004153482,0.000144156,0.0006924613,0.00005317365],"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":[0.001013041,0.0002993296,0.04166795,0.0003577004,0.0002378326,0.0007538063,0.0002925282,0.2370917,0.1771105,0.005842438,0.003818469,0.5315146],"study_design_scores_gemma":[0.000009816506,0.00006941862,0.006560876,0.000004648687,0.00002443621,0.00008929174,0.00001814888,0.9771529,0.01488827,0.000806806,0.000350897,0.00002436135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1858286,0.0002489457,0.8113239,0.0001630028,0.00005538073,0.00006756996,0.0001755813,0.0009841939,0.00115287],"genre_scores_gemma":[0.9075222,0.0001365712,0.09120999,0.00002631619,0.00002141604,0.00004164475,0.0001732969,0.00005163729,0.0008169319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004684014,"threshold_uncertainty_score":0.009313464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008785248475641463,"score_gpt":0.2185392953492826,"score_spread":0.2097540468736411,"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."}}