{"id":"W2123375513","doi":"10.1002/aic.14063","title":"Data‐driven model predictive quality control of batch processes","year":2013,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Model predictive control; Unavailability; Weighting; Computer science; Quality (philosophy); Process (computing); Batch processing; Nonlinear system; Trajectory; Process control; Control theory (sociology); Data mining; Control (management); Engineering; Reliability engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001073619,0.0007933186,0.0008410621,0.0003433864,0.0004026871,0.001044538,0.00113948,0.000576798,0.0006713505],"category_scores_gemma":[0.001994977,0.000483856,0.0004825769,0.0004673811,0.0008013234,0.0006538806,0.0007711455,0.001221239,0.0001296076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009643408,"about_ca_system_score_gemma":0.001053953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009840921,"about_ca_topic_score_gemma":0.005215263,"domain_scores_codex":[0.9995903,0.00008866356,0.00002030152,0.00008657268,0.0001715667,0.00004262506],"domain_scores_gemma":[0.999153,0.0004387004,0.0001493371,0.00005533053,0.0001819581,0.00002162873],"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":[0.000028661,0.0000115838,0.0001330892,0.00003325718,0.000007148085,0.00001335602,0.00001594014,0.9910502,0.001294739,0.001283527,0.0000943968,0.006034014],"study_design_scores_gemma":[0.000003204741,0.000009491497,0.00003519275,0.000001152288,0.00000136139,9.421832e-7,9.104683e-7,0.998939,0.0004693054,0.0004670114,0.00007094536,0.000001573958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03838005,0.00039818,0.9578188,0.0001753652,0.00004762556,0.00004756601,0.00008357558,0.0004082927,0.002640458],"genre_scores_gemma":[0.9765505,0.0002137627,0.0219096,0.00002717555,0.00001438808,0.0001020107,0.00008936691,0.00002004591,0.00107316],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009840921,"threshold_uncertainty_score":0.01956731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0233824593634312,"score_gpt":0.2671973362323493,"score_spread":0.2438148768689181,"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."}}