{"id":"W2001313745","doi":"10.2166/wst.2013.465","title":"Simulating future trends in urban stormwater quality for changing climate, urban land use and environmental controls","year":2013,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Impervious surface; Environmental science; Stormwater; Surface runoff; Low-impact development; Urbanization; Bioretention; Pollutant; Land use; Water quality; Environmental engineering; Hydrology (agriculture); Nonpoint source pollution; Water resource management; Stormwater management; Civil engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0005427465,0.0004887136,0.0003434151,0.0003856895,0.0003495834,0.000548668,0.0005920671,0.0008728124,0.001258246],"category_scores_gemma":[0.001150499,0.0002539309,0.0007721213,0.0006717776,0.0003523615,0.0004140919,0.0003424924,0.0003870656,0.0001032317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001491188,"about_ca_system_score_gemma":0.0009115343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05747718,"about_ca_topic_score_gemma":0.04723094,"domain_scores_codex":[0.9998102,0.00007663447,0.00001021553,0.00003308583,0.00002393234,0.00004592847],"domain_scores_gemma":[0.9994342,0.0002818744,0.00007062934,0.00003685053,0.0001084573,0.00006796355],"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":[0.000133676,0.00009490662,0.01974329,0.00001944382,0.00003204347,0.0001043011,0.00005320546,0.9773057,0.0009364121,0.0002479467,0.0001057114,0.001223299],"study_design_scores_gemma":[0.00007191613,0.0002361847,0.01672189,0.000004199351,0.00003692141,0.00002336521,0.0002119659,0.9808552,0.001256975,0.0002959246,0.0002694026,0.00001605164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987319,0.00000674249,0.0005496746,0.00002117639,0.000002956462,0.00001393098,0.0002571827,0.00002090804,0.000395471],"genre_scores_gemma":[0.9983669,0.00001604344,0.000880838,0.000004294247,0.000001602606,0.00002354051,0.0003637327,0.000005332272,0.0003379111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05747718,"threshold_uncertainty_score":0.1142852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01363580872206431,"score_gpt":0.2347909706909395,"score_spread":0.2211551619688752,"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."}}