{"id":"W2196218134","doi":"10.1016/j.ifacol.2015.09.022","title":"Model Predictive Control in Industry: Challenges and Opportunities","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":290,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Honeywell (Canada)","funders":"","keywords":"Automation; Usability; Workforce; Control (management); Model predictive control; Computer science; Work (physics); Risk analysis (engineering); Project commissioning; Process management; Engineering; Business; Publishing; Artificial intelligence","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":[0.005206152,0.0005258106,0.0007950546,0.0007525847,0.0008790867,0.004532391,0.001459794,0.004506037,0.003649255],"category_scores_gemma":[0.005494804,0.0002799221,0.0003131313,0.001598176,0.003178511,0.007784815,0.002155653,0.003647219,0.001076455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087289,"about_ca_system_score_gemma":0.003322565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001596662,"about_ca_topic_score_gemma":0.001759505,"domain_scores_codex":[0.9982223,0.0006148598,0.00006699612,0.0002076636,0.0006827005,0.0002054393],"domain_scores_gemma":[0.9963378,0.001993939,0.0001853413,0.0001769048,0.0009791678,0.0003269134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001365225,0.000294735,0.002853097,0.001159687,0.00003183197,0.0002892462,0.0005453657,0.0319804,0.001014379,0.2705847,0.03917369,0.6519363],"study_design_scores_gemma":[0.00004742077,0.0003946622,0.001502438,0.001354442,0.00002304725,0.0004380327,0.003824343,0.1615727,0.0009900548,0.5749456,0.2548068,0.0001005295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02821598,0.4087455,0.173207,0.3215207,0.00288457,0.00005604412,0.0001306138,0.0006803995,0.06455913],"genre_scores_gemma":[0.6164278,0.2869223,0.06602023,0.01022481,0.007069239,0.0001466729,0.0001979762,0.0001079282,0.01288302],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005206152,"threshold_uncertainty_score":0.02753311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07174965562319378,"score_gpt":0.2438944537197352,"score_spread":0.1721447980965414,"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."}}