{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001005212,0.0008235092,0.0009717835,0.0004632269,0.0004893325,0.001340183,0.0009087044,0.0008641013,0.00109288],"category_scores_gemma":[0.002286222,0.0003570892,0.0004237419,0.0006746321,0.0009573801,0.0005893784,0.0007346783,0.00100336,0.000106062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342458,"about_ca_system_score_gemma":0.001325129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02126708,"about_ca_topic_score_gemma":0.01010412,"domain_scores_codex":[0.9994817,0.0001964437,0.00001752472,0.00006137963,0.000165085,0.00007777291],"domain_scores_gemma":[0.9990031,0.0006274863,0.0001352507,0.00003104989,0.0001760509,0.00002712666],"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":[0.00001131555,0.00000664501,0.0000647791,0.00001283204,0.000004654661,0.00001009015,0.000003774218,0.9966154,0.0001228126,0.001592608,0.00006874307,0.001486333],"study_design_scores_gemma":[0.000003252331,0.00000498555,0.00003554194,9.304402e-7,0.000001302764,7.609393e-7,0.000001152711,0.999196,0.00006569186,0.0006151476,0.00007412982,0.000001090979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1623523,0.001877297,0.8093373,0.001168631,0.0002247333,0.0001281848,0.0002137825,0.0004203999,0.02427742],"genre_scores_gemma":[0.9919497,0.000339807,0.005590478,0.00004162972,0.00002364704,0.00006970602,0.0000567842,0.00001158903,0.001916694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02126708,"threshold_uncertainty_score":0.04228657,"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."}}