{"id":"W3160193680","doi":"10.14796/jwmm.c474","title":"Modeling a Bioretention Basin and Vegetated Swale with a Trapezoidal Cross Section using SWMM LID Controls","year":2021,"lang":"en","type":"article","venue":"Journal of Water Management Modeling","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"EXP (Canada); Polytechnique Montréal","funders":"","keywords":"Bioretention; Swale; Environmental science; Stormwater; Hydrology (agriculture); Inflow; Outflow; Stormwater management; Low-impact development; Hydraulic conductivity; Surface runoff; Geotechnical engineering; Soil science; Engineering; Soil water; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0006255816,0.0002132219,0.0002700308,0.0001877019,0.0002956438,0.0002651511,0.0001534307,0.00005826402,0.00009900575],"category_scores_gemma":[0.00000474242,0.000159897,0.0001113993,0.0002205315,0.00006267831,0.001091181,0.0002398907,0.000208481,0.00001037727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002694619,"about_ca_system_score_gemma":0.000008430966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001223078,"about_ca_topic_score_gemma":0.00004587587,"domain_scores_codex":[0.9980497,0.00008731907,0.0005911177,0.0003409701,0.0005311891,0.0003996719],"domain_scores_gemma":[0.9994578,0.000005892624,0.000146415,0.0001979751,0.00008126101,0.0001105964],"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":[0.0001256469,0.00008718273,0.002562585,0.00004568394,0.000195162,0.0001555308,0.0004875507,0.9705822,0.02531772,0.00002179022,0.00001322376,0.0004057043],"study_design_scores_gemma":[0.001756053,0.00009230789,0.0003704702,0.0001212546,0.0003348525,0.0001507909,0.0003623619,0.9943879,0.001465547,0.0004876755,0.0002405136,0.0002303283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6213341,0.00006214428,0.3777901,0.0001446171,0.0001267496,0.0001408961,8.603809e-7,0.00001950967,0.0003810121],"genre_scores_gemma":[0.9831645,0.00005890747,0.01609596,0.0001117597,0.00009382008,0.000005303697,0.000005930086,0.0000301767,0.0004335767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3618304,"threshold_uncertainty_score":0.6520408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000537702945557,"score_gpt":0.228375329041762,"score_spread":0.2083699520123064,"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."}}