{"id":"W2395498647","doi":"10.1061/9780784479889.041","title":"Physical Scale and Computational Modeling in the Development of a Vortex-Type Stormwater Retention Pond","year":2016,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2016","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Environmental Protection Agency","keywords":"Berm; Inlet; Deposition (geology); Sediment; Computational fluid dynamics; Environmental science; Residence time (fluid dynamics); Flow (mathematics); Hydrology (agriculture); Fluent; Stormwater; Vortex; Geology; Surface runoff; Geotechnical engineering; Engineering; Meteorology; Geomorphology; Mechanics; Geography","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":[0.0002074164,0.0001416709,0.0001280056,0.00006345864,0.0001449448,0.0000224073,0.0001419595,0.00002344648,0.0002960521],"category_scores_gemma":[9.039252e-7,0.00006881844,0.00002486739,0.00004465891,0.0003747139,0.0002217791,0.0003264364,0.0000560158,0.0001220642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007098206,"about_ca_system_score_gemma":0.000001159368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004663763,"about_ca_topic_score_gemma":0.0001809341,"domain_scores_codex":[0.9989089,0.00006122471,0.0002329072,0.000285295,0.000279461,0.0002321744],"domain_scores_gemma":[0.9997472,0.00002497534,0.00004300888,0.0001336696,0.000001378781,0.00004976501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002111953,0.0005173734,0.7899291,0.00004031958,0.00007352992,0.00001059546,0.0335732,0.002049747,0.1376511,0.00005325665,0.0004642825,0.03542628],"study_design_scores_gemma":[0.003452451,0.0002130204,0.8997931,0.0002397848,0.0001041611,0.00002270749,0.001259784,0.02595648,0.01068701,0.005168214,0.05207054,0.001032745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985163,0.00003798667,0.0002835851,0.0003004206,0.00003528337,0.0001870781,0.000006235844,0.000009538604,0.0006235217],"genre_scores_gemma":[0.996549,0.000009692089,0.0004448305,0.00004890743,0.00001657665,0.00001734418,0.000009916434,0.0000103262,0.002893375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1269641,"threshold_uncertainty_score":0.3241563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01476919580684722,"score_gpt":0.1954310345869311,"score_spread":0.1806618387800839,"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."}}