{"id":"W3210257371","doi":"10.32920/ryerson.14661456.v1","title":"Stormwater management: municipal policies in Ontario for managing rain where it falls through green infrastructure","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Stormwater; Green infrastructure; Environmental planning; Surface runoff; Flooding (psychology); Stormwater management; Low-impact development; Business; Urban planning; Environmental resource management; Environmental science; Civil engineering; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00032786,0.0006442157,0.0005674148,0.0002021689,0.0002198973,0.0002880634,0.001320107,0.0003335344,0.008178634],"category_scores_gemma":[0.000005338709,0.0006303259,0.000285546,0.0002663509,0.0002125679,0.0005935811,0.006916232,0.0008283345,0.0001447161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002754077,"about_ca_system_score_gemma":0.00003337267,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5467473,"about_ca_topic_score_gemma":0.8938724,"domain_scores_codex":[0.996443,0.00009315088,0.0006717257,0.001243465,0.000562646,0.0009859595],"domain_scores_gemma":[0.9983222,0.00003226814,0.0002024646,0.001324739,0.00001358188,0.0001047108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001583503,0.0006166463,0.3616979,0.001933173,0.001614452,0.0003905965,0.1493737,0.1826404,0.0002092444,0.01026915,0.2856295,0.005466901],"study_design_scores_gemma":[0.001781261,0.00007228941,0.2783568,0.0004753954,0.000340748,0.000007336451,0.009243363,0.002342082,0.00004223643,0.03257227,0.6728945,0.001871674],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4267952,0.0002020209,0.02186698,0.005521107,0.001346207,0.004648629,0.00007156725,0.0003202779,0.5392281],"genre_scores_gemma":[0.5194703,0.0003238757,0.1020536,0.004328613,0.00018285,0.001306845,0.000796391,0.0002078152,0.3713298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.387265,"threshold_uncertainty_score":0.9996148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02435186489684764,"score_gpt":0.248155284104805,"score_spread":0.2238034192079573,"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."}}