{"id":"W2913985039","doi":"10.1061/(asce)hy.1943-7900.0001581","title":"Modeling Performance of Sediment Control Wet Ponds at Two Construction Sites in Ontario, Canada","year":2019,"lang":"en","type":"article","venue":"Journal of Hydraulic Engineering","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Fluidigm (Canada); University of Guelph","funders":"U.S. Army Corps of Engineers; Division of Ocean Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Sediment; Retention basin; Hydrology (agriculture); Environmental science; Stormwater; Sediment control; Storm; Outflow; Sediment transport; STREAMS; Drawdown (hydrology); Surface runoff; Geotechnical engineering; Geology; Ecology; Geomorphology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001932579,0.00009321731,0.0001822832,0.0000840795,0.0000201585,0.000005630063,0.000127757,0.00001956999,0.0005266502],"category_scores_gemma":[0.000005874075,0.00008896349,0.00003904747,0.00009909934,0.00001267596,0.0002602446,0.00005853583,0.0001697339,0.000009284655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001642082,"about_ca_system_score_gemma":0.00004424054,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.323228,"about_ca_topic_score_gemma":0.5188,"domain_scores_codex":[0.9990421,0.000008264377,0.0003683918,0.00008657808,0.0003141112,0.0001805685],"domain_scores_gemma":[0.9996938,0.00001580356,0.0001214366,0.0001033263,0.00001001041,0.00005563691],"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":[0.000012651,0.000007889192,0.25969,0.000008135986,0.00001496124,0.000004082554,0.0000877697,0.7270703,0.01299353,0.000006387434,0.00007755079,0.00002672601],"study_design_scores_gemma":[0.0009804051,0.00007165697,0.08112349,0.00005662803,0.00002108151,0.00004419376,0.00003089396,0.9152617,0.001198311,0.000003534318,0.001092464,0.0001155952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973122,0.0000313252,0.001330684,0.00005605104,0.0002772504,0.00008660355,8.424479e-7,0.000004542268,0.0009004739],"genre_scores_gemma":[0.9987116,0.000004116012,0.001016621,0.00003406867,0.00001784463,0.000001303501,8.297999e-7,0.000007834861,0.0002057797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.195572,"threshold_uncertainty_score":0.6812787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00427494227855193,"score_gpt":0.1579194988525623,"score_spread":0.1536445565740104,"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."}}