{"id":"W2547393114","doi":"10.1680/jenes.15.00017","title":"A storm water basin model using settling velocity distribution","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Settling; Environmental science; Sampling (signal processing); Storm; Hydrology (agriculture); Water quality; Structural basin; Particle (ecology); Calibration; Total suspended solids; Drainage basin; Suspended solids; Geology; Environmental engineering; Geomorphology; Oceanography; Wastewater; Geotechnical engineering; Mathematics; Statistics; Ecology; Computer science; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002521329,0.000666805,0.0006385634,0.0003874996,0.0006763117,0.0009783785,0.001310994,0.001403178,0.003690606],"category_scores_gemma":[0.0007416048,0.0004649579,0.0007154257,0.0005291702,0.0004151392,0.0008562804,0.0006083669,0.0006750562,0.0004617823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001015256,"about_ca_system_score_gemma":0.001483238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04999158,"about_ca_topic_score_gemma":0.01900086,"domain_scores_codex":[0.9998894,0.00001790474,0.00000884176,0.00003630113,0.00002859994,0.00001898014],"domain_scores_gemma":[0.9998201,0.00007320854,0.00002240028,0.00001356163,0.00005432154,0.00001647529],"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":[0.00001108744,0.00001014484,0.0004112519,0.000009232581,0.000007750863,0.00002065358,0.00001115715,0.9963452,0.0005740357,0.001159818,0.00016369,0.001276047],"study_design_scores_gemma":[0.000004765232,0.000003794731,0.0000859202,8.598012e-7,0.000001993763,0.000003349503,0.000002140423,0.9992712,0.00007758594,0.0002989997,0.0002474505,0.000001820821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3535351,0.000402762,0.610582,0.0006908536,0.0001252326,0.0003693066,0.004450323,0.002640958,0.02720345],"genre_scores_gemma":[0.9405034,0.0003736252,0.03744604,0.00007759561,0.00003438891,0.00057673,0.001743009,0.0002075929,0.0190376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04999158,"threshold_uncertainty_score":0.09940118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00936718296683208,"score_gpt":0.1830242838389555,"score_spread":0.1736571008721234,"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."}}