{"id":"W2508166680","doi":"10.1021/ie504995n","title":"Economic Model Predictive Control of Wastewater Treatment Processes","year":2015,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Benchmark (surveying); Model predictive control; Effluent; Sewage treatment; Computer science; Wastewater; Work (physics); Control (management); Operating cost; Quality (philosophy); Component (thermodynamics); Process engineering; Environmental science; Environmental engineering; Engineering; Waste management; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003218318,0.0002004713,0.000321153,0.00008745846,0.00002368247,0.0000307764,0.0002042867,0.0002292998,0.00001103846],"category_scores_gemma":[0.0002862619,0.0001972496,0.00004275857,0.0001849823,0.00004083707,0.0001711229,0.00002666587,0.0002929267,0.00001028873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009064777,"about_ca_system_score_gemma":0.0003449868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001906355,"about_ca_topic_score_gemma":9.296017e-7,"domain_scores_codex":[0.9987048,0.00001798816,0.0003433876,0.0002192529,0.0002940084,0.0004205654],"domain_scores_gemma":[0.9991333,0.000133102,0.00003593206,0.0002846453,0.0002039768,0.0002090421],"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":[0.00007179797,0.00001544707,0.00005421868,0.0000841515,0.00008109387,0.000002350098,0.0001118559,0.863053,0.1362575,0.000006696832,0.0001533156,0.0001085743],"study_design_scores_gemma":[0.001778733,0.00005737987,5.550988e-7,0.00005016154,0.00001059315,0.000003229176,0.00005000046,0.6715203,0.3259661,0.00001630026,0.0004373022,0.0001093313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438531,0.001481372,0.04318958,0.0001331426,0.0007313039,0.00209926,0.0004869907,0.001098933,0.006926251],"genre_scores_gemma":[0.9987976,0.00002219542,0.00009817121,3.251376e-7,0.0005131806,0.0002025765,0.00002166075,0.00005774464,0.000286539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1915327,"threshold_uncertainty_score":0.8043606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07046311081130412,"score_gpt":0.2947063463914721,"score_spread":0.224243235580168,"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."}}