{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005260111,0.0008198665,0.0009533818,0.0003675792,0.0004045457,0.0009011268,0.0009704424,0.0007809146,0.006018576],"category_scores_gemma":[0.001116884,0.0004040138,0.0007444076,0.0006303209,0.0003807952,0.0006223488,0.001083069,0.001161169,0.001633251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003412869,"about_ca_system_score_gemma":0.0007630206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009298681,"about_ca_topic_score_gemma":0.007527651,"domain_scores_codex":[0.9996892,0.00006385228,0.00002047206,0.00006941557,0.0001251829,0.00003184563],"domain_scores_gemma":[0.99966,0.0001068073,0.00003840779,0.00006550305,0.0001175422,0.00001176415],"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":[0.00006686444,0.00003165596,0.0002012787,0.0001142752,0.00004450518,0.00004291548,0.00002876065,0.9061707,0.001855713,0.005582287,0.001864288,0.08399678],"study_design_scores_gemma":[0.000008991146,0.00002423513,0.00005086957,0.000005848799,0.000004704943,0.000004892016,0.000002150828,0.9954492,0.0005088574,0.001890892,0.002045505,0.00000374008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004438607,0.0003204565,0.9840789,0.0001444149,0.0001590647,0.00005147917,0.0001475464,0.00200254,0.008656962],"genre_scores_gemma":[0.7627008,0.0006368061,0.2134458,0.0002740215,0.0001597314,0.0005987719,0.0007537391,0.0002947387,0.02113562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009298681,"threshold_uncertainty_score":0.02013415,"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."}}