{"id":"W2555463464","doi":"10.1002/aic.15592","title":"Linear model predictive control for transport‐reaction processes","year":2016,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Discretization; Linear-quadratic regulator; Partial differential equation; Optimal control; Model predictive control; Mathematical optimization; Applied mathematics; Mathematics; Controller (irrigation); Linear system; Computer science; Control theory (sociology); Control (management); Mathematical analysis","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":[0.0002061149,0.0001096753,0.0001676466,0.00005544964,0.00006592656,0.000009070225,0.00007319909,0.00007859363,0.000004181971],"category_scores_gemma":[0.0001028012,0.00007610911,0.00006590955,0.00005993074,0.00001277763,0.000540248,0.000001180439,0.0001057012,0.000004522394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009299966,"about_ca_system_score_gemma":0.00005690162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.581351e-7,"about_ca_topic_score_gemma":0.000004444117,"domain_scores_codex":[0.9992858,0.00001309651,0.0003077683,0.00009281263,0.0001142438,0.000186338],"domain_scores_gemma":[0.9993863,0.00009058928,0.00009492135,0.000076219,0.0002694026,0.00008263841],"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":[0.0001294708,0.00001372174,0.0004979289,0.0000428276,0.0001094196,0.000001288487,0.0000895964,0.9775528,0.0165652,0.00003710551,0.0003050031,0.004655646],"study_design_scores_gemma":[0.00329429,0.00009475328,0.0003056644,0.0001003915,0.00007969925,0.00003906458,0.00002110522,0.9921502,0.001178176,0.001170191,0.001419053,0.0001474049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00461604,0.0002702328,0.9938613,0.0001523439,0.0003254226,0.0002858388,0.00003927777,0.0001552691,0.0002943449],"genre_scores_gemma":[0.9923406,0.0002471844,0.006429256,0.00002875585,0.0006318683,0.00005519464,0.000002260007,0.00004015506,0.0002247531],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9877245,"threshold_uncertainty_score":0.3103639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008041387498866726,"score_gpt":0.2158509656683381,"score_spread":0.2078095781694713,"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."}}