{"id":"W4386157770","doi":"10.32920/24034101.v1","title":"Evaluation of the Storm Water Volume Control Target in Ontario","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Percentile; Environmental science; Storm; Volume (thermodynamics); Hydrology (agriculture); Stormwater; Event (particle physics); Stormwater management; Meteorology; Surface runoff; Statistics; Geography; Mathematics; Geology","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":[0.001350685,0.0003387686,0.0002521764,0.0004025121,0.0008210361,0.001064324,0.0008394032,0.0003242615,0.001192012],"category_scores_gemma":[0.003268902,0.0001686881,0.0002340425,0.0006272203,0.000705045,0.0004418156,0.0005480683,0.0002059707,0.0001518444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01895485,"about_ca_system_score_gemma":0.01608148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8980269,"about_ca_topic_score_gemma":0.9116172,"domain_scores_codex":[0.9976074,0.0002402616,0.00005596501,0.0001299776,0.001597373,0.0003689533],"domain_scores_gemma":[0.9979437,0.0002849774,0.0002840289,0.0001047681,0.001208669,0.0001737375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002187148,0.0007347073,0.1849606,0.0004797951,0.0001225939,0.0006734284,0.002138885,0.5704703,0.07437565,0.01154148,0.01018206,0.1421333],"study_design_scores_gemma":[0.0006091226,0.003716509,0.4406407,0.00007873749,0.000156973,0.000183946,0.004372501,0.3927487,0.102182,0.002020685,0.05311586,0.0001743461],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634396,0.0001441142,0.006416828,0.0003251561,0.00001312641,0.0003437053,0.000814675,0.0002205913,0.02828223],"genre_scores_gemma":[0.9945475,0.00007567993,0.001555189,0.00002552631,0.000003005536,0.00004525119,0.0004019693,0.00001375854,0.003332189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1019731,"threshold_uncertainty_score":0.2051471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04710709459069608,"score_gpt":0.2379024779486283,"score_spread":0.1907953833579322,"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."}}