{"id":"W1995013804","doi":"10.1002/cjce.5450800519","title":"Assessing the Performance of Model Predictive Controllers","year":2002,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shell (Canada); University of Alberta","funders":"","keywords":"Model predictive control; Metric (unit); Computer science; Statistic; Control theory (sociology); Function (biology); Measure (data warehouse); Value (mathematics); Relevance (law); Performance metric; Mathematical optimization; Control (management); Mathematics; Engineering; Artificial intelligence; Machine learning; Data mining; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.006504663,0.0009927308,0.0007344235,0.0009270643,0.0003252618,0.001472107,0.0006009524,0.001342579,0.0006057102],"category_scores_gemma":[0.02513862,0.000185832,0.0002969987,0.0005532283,0.0006853561,0.001226488,0.0007879558,0.0005512239,0.0001435822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007017219,"about_ca_system_score_gemma":0.0007165246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001707517,"about_ca_topic_score_gemma":0.000648419,"domain_scores_codex":[0.9962353,0.001761568,0.000211249,0.000363096,0.001237339,0.0001913675],"domain_scores_gemma":[0.9870458,0.009310134,0.001151791,0.0008315075,0.001484908,0.000175867],"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":[0.0004478881,0.0001099211,0.004064478,0.00008596741,0.00008443459,0.00005296263,0.00003076203,0.9407987,0.006591243,0.002758923,0.0002612773,0.04471341],"study_design_scores_gemma":[0.00001280642,0.0004542624,0.002009605,0.000008558041,0.00001439484,0.00002141224,0.00001633782,0.9885334,0.006836395,0.001944296,0.0001309396,0.00001753385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6023551,0.0009522691,0.3909884,0.0003201009,0.00005866891,0.00008228774,0.0001309958,0.0006637204,0.004448337],"genre_scores_gemma":[0.9923726,0.00004144283,0.007267307,0.00001542178,0.00001041222,0.00001773307,0.00007485243,0.00001427087,0.0001859194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006504663,"threshold_uncertainty_score":0.0344004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008935424065567809,"score_gpt":0.1842114629014157,"score_spread":0.1752760388358479,"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."}}