{"id":"W189026918","doi":"","title":"LINEAR AND NONLINEAR MODEL PREDICTIVE CONTROL DESIGN FOR A MILK PASTEURIZATION PLANT","year":2003,"lang":"en","type":"article","venue":"Control and Intelligent Systems","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Model predictive control; Control theory (sociology); Benchmark (surveying); PID controller; Nonlinear system; Artificial neural network; Linear model; Controller (irrigation); Operating point; Nonlinear model; Smith predictor; Control engineering; Engineering; Computer science; Temperature control; Control (management); Artificial intelligence; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003907747,0.0002730202,0.0004704952,0.0001023703,0.000107162,0.00006517601,0.00006425756,0.0001501326,0.000001127609],"category_scores_gemma":[0.0001466456,0.0002472963,0.00005068667,0.00007067656,0.00003377331,0.00019477,0.000004675022,0.00009492019,0.000003204165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005912525,"about_ca_system_score_gemma":0.0000233045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004380247,"about_ca_topic_score_gemma":0.000001456102,"domain_scores_codex":[0.9986289,0.0001135219,0.0005096333,0.0002985175,0.0001375961,0.0003118761],"domain_scores_gemma":[0.9991426,0.0002878178,0.0001057022,0.0001646167,0.0001561274,0.0001430789],"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":[0.0001633487,0.00001478738,0.0001042075,0.0001618285,0.0001346338,0.000001012511,0.0001685394,0.9949076,0.001975436,0.001946386,0.0001083162,0.0003138858],"study_design_scores_gemma":[0.002760123,0.0001691978,0.000005805216,0.00009377085,0.00009322087,0.00002053159,0.0001319457,0.9939039,0.0003834666,0.0001715621,0.002023189,0.0002432382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006743229,0.005894326,0.9897696,0.00001921538,0.0004373196,0.002592606,0.0002461027,0.0001942892,0.0001722562],"genre_scores_gemma":[0.9936621,0.0003415406,0.004916909,0.00004687356,0.0001893572,0.0006029526,0.00002847418,0.00006416645,0.0001476227],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9929878,"threshold_uncertainty_score":0.9999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526936733743735,"score_gpt":0.2098473493727142,"score_spread":0.1945779820352769,"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."}}