{"id":"W2321190477","doi":"10.1061/40685(2003)294","title":"Least-Cost Design of Urban Drainage Systems for Various Levels of Quantity and Quality Management","year":2003,"lang":"en","type":"article","venue":"","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Drainage; Stormwater; Flooding (psychology); Stormwater management; Environmental science; Drainage system (geomorphology); Pollutant; Best practice; Computer science; Water quality; Downstream (manufacturing); Environmental engineering; Civil engineering; Water resource management; Engineering; Surface runoff; Operations management; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001076033,0.0001210468,0.0002170153,0.00005094161,0.00008603055,0.0000168126,0.000166027,0.00003687093,0.0002179033],"category_scores_gemma":[0.00003427285,0.0001104052,0.00004568292,0.0001603071,0.0001850689,0.0001600395,0.000118905,0.0000314196,0.00001971869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009057431,"about_ca_system_score_gemma":0.000003979455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009952536,"about_ca_topic_score_gemma":0.00008095394,"domain_scores_codex":[0.9987285,0.0001475947,0.000371333,0.0002748571,0.0002469227,0.0002308326],"domain_scores_gemma":[0.9993609,0.00008153363,0.0001562748,0.0003330559,0.00001182817,0.00005641521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00006978614,0.0006284667,0.1202617,0.0008689084,0.0002416792,0.000003133658,0.000970296,0.01138386,0.007158272,0.8458679,0.01176717,0.0007787708],"study_design_scores_gemma":[0.005224315,0.0007553954,0.9067233,0.0001199393,0.0005059744,0.000007152866,0.002940956,0.01197238,0.006894558,0.008752328,0.05471907,0.001384615],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03166806,0.0000905389,0.9221226,0.00002161883,0.0001129584,0.001889197,0.00004124499,0.00003372477,0.04402003],"genre_scores_gemma":[0.9778889,0.000008692092,0.01518234,0.000023919,0.000003515499,0.00006904588,0.0000018241,0.000009932374,0.006811762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9462209,"threshold_uncertainty_score":0.4502194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08168635128301267,"score_gpt":0.2746019997406168,"score_spread":0.1929156484576041,"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."}}