{"id":"W4244209715","doi":"10.32920/ryerson.14645739.v1","title":"Analytical hydrological modelling of green roof technology on a watershed basis","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Toronto Metropolitan University","funders":"","keywords":"Watershed; Surface runoff; Green roof; Low-impact development; Environmental science; Stormwater management; Stormwater; Range (aeronautics); Hydrology (agriculture); Civil engineering; Roof; Computer science; Engineering; Geotechnical engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001888461,0.000356244,0.0002523642,0.0004715806,0.000329299,0.0008195516,0.0005665756,0.0004488076,0.002055679],"category_scores_gemma":[0.0005858436,0.0002399551,0.0003600221,0.0007535259,0.0004086746,0.0005854004,0.000255021,0.0002980906,0.0002342128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002399593,"about_ca_system_score_gemma":0.001867763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.108439,"about_ca_topic_score_gemma":0.09617811,"domain_scores_codex":[0.9998891,0.00001801075,0.00000552528,0.0000259809,0.00003677025,0.00002466901],"domain_scores_gemma":[0.9998689,0.00004918324,0.00001704126,0.00001121199,0.00004653805,0.00000724174],"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":[0.000008768164,0.0000213858,0.001603742,0.00001750282,0.00000634923,0.00002813282,0.00003429632,0.9884076,0.002802151,0.001718171,0.000171085,0.005180873],"study_design_scores_gemma":[0.000003651403,0.000006132843,0.0009816639,0.000001618359,0.000002966475,0.00000511235,0.00001554862,0.996681,0.0009175075,0.0007116612,0.0006694332,0.000003743623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7880459,0.0001869046,0.1767669,0.000344601,0.00002956139,0.0001625033,0.002093026,0.001168375,0.03120215],"genre_scores_gemma":[0.9830957,0.0001727751,0.01188635,0.000017493,0.000007777692,0.00005218368,0.0003770452,0.00005888369,0.004331796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.108439,"threshold_uncertainty_score":0.2156157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03751999151174633,"score_gpt":0.2319662441898969,"score_spread":0.1944462526781506,"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."}}