{"id":"W4362722114","doi":"10.1016/j.compag.2023.107820","title":"Closed-loop operation of a simulated recirculating aquaculture system with an integrated application of nonlinear model predictive control and moving horizon estimation","year":2023,"lang":"en","type":"article","venue":"Computers and Electronics in Agriculture","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Control theory (sociology); Nonlinear system; Water quality; Recirculating aquaculture system; Controller (irrigation); Closed loop; Noise (video); Engineering; Environmental science; Environmental engineering; Control engineering; Computer science; Aquaculture; Control (management); Fish <Actinopterygii>; Ecology","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":[0.000122523,0.000152492,0.0002710198,0.00008854074,0.00004479931,0.00002274618,0.00005564219,0.0001358198,3.39646e-8],"category_scores_gemma":[0.000009677657,0.0001133354,0.00001484205,0.0004291681,0.00001616465,0.0002394884,0.000009544427,0.0001623559,8.129405e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001182547,"about_ca_system_score_gemma":0.00001697288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003370864,"about_ca_topic_score_gemma":0.00006700878,"domain_scores_codex":[0.9991937,0.00003560188,0.0003025978,0.000201304,0.0001144626,0.0001523627],"domain_scores_gemma":[0.9995646,0.00003728752,0.0001226995,0.00009490173,0.0001461811,0.00003430505],"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":[0.00004369386,0.00001034278,0.0002095253,0.0001621248,0.00003495199,4.439748e-7,0.0004376989,0.9698562,0.02302236,0.0005803006,0.000003314477,0.005639041],"study_design_scores_gemma":[0.0009542817,0.0002137951,0.0005096445,0.0002108593,0.00002693408,0.000004974114,0.0002585152,0.99725,0.000410688,0.00003581471,0.000002688254,0.0001218087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.323692,0.0002424721,0.6754318,0.000006841264,0.00001462542,0.0004561558,0.00001374169,0.0001334168,0.000008936528],"genre_scores_gemma":[0.9884702,0.00005024299,0.01116865,0.000002206859,0.0000198091,0.00002466743,0.0002452597,0.00001651268,0.000002429884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6647782,"threshold_uncertainty_score":0.4621685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003297167144631957,"score_gpt":0.195192489168321,"score_spread":0.1918953220236891,"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."}}