{"id":"W974850608","doi":"10.14796/jwmm.r241-14","title":"Model Predictive Control with SWMM","year":2011,"lang":"en","type":"article","venue":"Journal of Water Management Modeling","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung","keywords":"Model predictive control; Volume (thermodynamics); Control volume; Computer science; Control (management); Real-time Control System; Mechanics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004698186,0.0001821624,0.000205566,0.0001531542,0.0001235056,0.00003284926,0.0004262728,0.00003284071,0.0003971363],"category_scores_gemma":[0.000001663509,0.0001128257,0.00009436064,0.0000963015,0.00007064817,0.0008087283,0.0002272795,0.0001627863,0.0001264895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001830796,"about_ca_system_score_gemma":0.000003631561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002602269,"about_ca_topic_score_gemma":0.000008183065,"domain_scores_codex":[0.9983804,0.00003387491,0.0004403584,0.0002180756,0.0005465882,0.0003807515],"domain_scores_gemma":[0.9994387,0.000003569844,0.000153418,0.0002547736,0.00003341795,0.0001160974],"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":[0.0002669949,0.0001478919,0.002911344,0.00001206981,0.0002500863,0.00008100064,0.001706011,0.9930243,0.0002843222,0.000238902,0.000837595,0.0002395098],"study_design_scores_gemma":[0.001438403,0.0002443552,0.0005390727,0.00003710834,0.0003679078,0.00001823445,0.0003245417,0.9911596,0.0002641731,0.005075107,0.0003247442,0.0002067905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1597569,0.00001045726,0.7930291,0.0001286359,0.00008402679,0.000243065,0.00000141598,0.0000298968,0.04671657],"genre_scores_gemma":[0.9705089,0.00001398723,0.02777481,0.0002271942,0.0000360555,0.00001205592,0.000001001434,0.00002489239,0.001401088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.810752,"threshold_uncertainty_score":0.4600899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706013566529842,"score_gpt":0.190557477169442,"score_spread":0.1634973415041436,"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."}}