{"id":"W2897908033","doi":"10.1021/acs.iecr.8b02738","title":"Adaptive Model Predictive Batch Process Monitoring and Control","year":2018,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Model predictive control; Computer science; Process (computing); Controller (irrigation); Subspace topology; Identification (biology); Batch processing; Process control; Adaptive control; Control theory (sociology); Control engineering; Control (management); Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008578168,0.0006983824,0.0008332085,0.0003760131,0.0004316583,0.001013302,0.001551062,0.0006655808,0.000874891],"category_scores_gemma":[0.001834611,0.0003050498,0.0003945516,0.0005668412,0.0005689955,0.0008741091,0.0007924783,0.00125879,0.0002677058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007383071,"about_ca_system_score_gemma":0.0008774034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006054127,"about_ca_topic_score_gemma":0.003185958,"domain_scores_codex":[0.9993861,0.0001071567,0.00002646952,0.0001759333,0.0002536272,0.00005070179],"domain_scores_gemma":[0.999223,0.0003485268,0.0001302866,0.0001175413,0.0001610989,0.00001954147],"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":[0.0003384851,0.00018035,0.001410082,0.0001697261,0.00006436291,0.0001047942,0.00009996789,0.7360058,0.02327804,0.007373651,0.001807039,0.2291676],"study_design_scores_gemma":[0.000004205248,0.00003454904,0.0002029019,0.000002000841,0.000004056546,0.000009040195,0.00000289988,0.9960157,0.002582301,0.0008225717,0.0003151388,0.000004542779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02073037,0.0004083513,0.9757692,0.0001178251,0.00004814039,0.00004626999,0.00005170886,0.00100102,0.001827011],"genre_scores_gemma":[0.9404965,0.0002765348,0.05653052,0.00005571225,0.00003876736,0.0001138936,0.0001048415,0.00004382424,0.002339405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006054127,"threshold_uncertainty_score":0.01203781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05355759598640571,"score_gpt":0.3107978294538275,"score_spread":0.2572402334674218,"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."}}