{"id":"W2076025923","doi":"10.1016/s0009-2509(03)00077-0","title":"Model predictive control relevant identification and validation","year":2003,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Syncrude (Canada); University of Alberta","funders":"","keywords":"Model predictive control; Identification (biology); Computer science; Mean squared prediction error; Filter (signal processing); Predictive modelling; System identification; Data mining; Control (management); Algorithm; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025905,0.00008488703,0.00008560312,0.00007205191,0.00004063289,0.00005961557,0.00008608566,0.00004128156,0.000001772469],"category_scores_gemma":[0.0002366401,0.00008621202,0.00001664367,0.0002386723,0.00005577097,0.0002204131,0.000005279685,0.00008918945,0.000006639169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008160483,"about_ca_system_score_gemma":0.00001487261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.98898e-7,"about_ca_topic_score_gemma":1.994613e-8,"domain_scores_codex":[0.9993242,0.000003570845,0.0001483678,0.0001746438,0.0001747818,0.0001744539],"domain_scores_gemma":[0.999702,0.00002497912,0.00001472754,0.0001248802,0.00003899415,0.00009437855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.695057e-7,0.000001731379,0.00000891171,0.00001053283,0.000002272,1.089725e-7,0.00003045686,0.3550296,0.6440853,0.0007047085,0.000008614886,0.0001170158],"study_design_scores_gemma":[0.0001503246,0.000003021819,0.0000588822,0.000007823704,0.000003873158,0.000006069408,0.000007015969,0.7266186,0.2729356,0.00006977822,0.00006842877,0.00007055941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4856275,0.0001103975,0.5128155,0.00001630386,0.0002900409,0.0001306318,0.000003335595,0.0003521551,0.0006541703],"genre_scores_gemma":[0.9993045,0.000005264204,0.0005964969,0.000006835774,0.00001936219,0.00002989532,5.974465e-7,0.00001064613,0.00002636348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5136771,"threshold_uncertainty_score":0.3515624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006200604243724472,"score_gpt":0.1988287387950397,"score_spread":0.1926281345513152,"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."}}