{"id":"W2965889521","doi":"10.1016/j.jhydrol.2019.124000","title":"An integrated optimization and rule-based approach for predictive real time control of urban stormwater management systems","year":2019,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Stormwater; Detention basin; Environmental science; Outflow; Surface runoff; Real-time Control System; Low-impact development; Hydrology (agriculture); Structural basin; Computer science; Control (management); Meteorology; Stormwater management; Engineering; Geology","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":[0.0005077173,0.0001117228,0.0002791317,0.0001352098,0.00004000361,0.00001485724,0.0001914855,0.00007079849,0.0001262896],"category_scores_gemma":[0.000004667912,0.00008692929,0.00005333392,0.00008201979,0.0001145196,0.0002557949,0.00003407782,0.00008065303,0.000008781347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000139282,"about_ca_system_score_gemma":0.000007783569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000435724,"about_ca_topic_score_gemma":0.000001036234,"domain_scores_codex":[0.9989454,0.0001309401,0.000378376,0.0001740256,0.0001883803,0.0001829289],"domain_scores_gemma":[0.999328,0.00003441644,0.0003701914,0.0001645579,0.00003393874,0.00006894198],"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":[0.0004477519,0.0001826841,0.02868138,0.00003327777,0.0001312675,0.000002669463,0.0001294736,0.9665735,0.002492888,0.00006133152,0.001204949,0.00005882698],"study_design_scores_gemma":[0.002420089,0.001481777,0.004746456,0.0000108988,0.0001717572,0.00001199276,0.00007472831,0.9898092,0.00005892566,0.0000219362,0.001102022,0.00009027736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4006561,0.00003059212,0.5958399,0.00007050789,0.0001512279,0.0008277532,0.00002339908,0.00001589513,0.002384593],"genre_scores_gemma":[0.9866906,0.00000650013,0.01274019,0.00004856374,0.00003120842,0.00001978506,0.00002427663,0.00001342082,0.0004254539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5860345,"threshold_uncertainty_score":0.3544873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004660971358553508,"score_gpt":0.1893070816962833,"score_spread":0.1846461103377298,"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."}}