{"id":"W2023477124","doi":"10.1002/cjce.20194","title":"Enhanced model predictive control of a catalytic flow reversal reactor","year":2009,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Polytechnique Montréal","funders":"","keywords":"Methane; Model predictive control; Continuous stirred-tank reactor; Plug flow reactor model; Volumetric flow rate; Combustion; Inert; Catalysis; Inlet; Energy balance; Catalytic combustion; Chemistry; Control theory (sociology); Nuclear engineering; Mechanics; Thermodynamics; Engineering; Computer science; Physics; Physical chemistry; Control (management); Mechanical engineering; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001342458,0.000131232,0.0002824549,0.0001088171,0.00001552471,0.00001349792,0.0002184568,0.00007956012,0.00000290922],"category_scores_gemma":[0.0002015799,0.0001111398,0.00008699008,0.000133573,0.00002317052,0.0001583765,0.000002230707,0.0002874343,7.537359e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003170062,"about_ca_system_score_gemma":0.0001508751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003533123,"about_ca_topic_score_gemma":0.00001778643,"domain_scores_codex":[0.9991698,0.000006260519,0.0003762847,0.00006077063,0.0001466784,0.0002401985],"domain_scores_gemma":[0.9993163,0.00005863914,0.00009422065,0.0001459742,0.000130968,0.0002539222],"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":[0.00001277819,0.000001518486,9.114606e-7,0.00001189078,0.00004066165,0.000003702131,0.0001870368,0.8021505,0.1971293,0.00008567099,0.00003240415,0.0003436457],"study_design_scores_gemma":[0.0005224413,0.00002687477,0.00000936131,0.00009767748,0.00004122529,0.00003083009,0.000005098769,0.9300977,0.06893776,0.0001224637,0.00001455798,0.00009402757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0412639,0.0005629504,0.9572935,0.000150325,0.0002014963,0.0001515535,0.00002568012,0.00003927969,0.0003113006],"genre_scores_gemma":[0.9976504,0.000002717529,0.002141256,0.00002402716,0.0001499951,0.000002157551,0.00000168613,0.00002264249,0.000005064579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9563866,"threshold_uncertainty_score":0.4532149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003521578953037826,"score_gpt":0.1654072616376433,"score_spread":0.1618856826846055,"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."}}