{"id":"W2049657078","doi":"10.1002/hyp.7904","title":"Stormwater quantity and quality response to climate change using artificial neural networks","year":2010,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Environmental science; Stormwater; Downscaling; Surface runoff; Climate change; Precipitation; Hydrology (agriculture); Turbidity; Storm; Water quality; Meteorology; Geography; 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":[0.0005099387,0.0004077344,0.0002093173,0.0005260805,0.0001415125,0.0005375223,0.0003352453,0.0004107301,0.0006449831],"category_scores_gemma":[0.001505255,0.0001478086,0.000346839,0.000615723,0.0001391995,0.0004337936,0.0002308679,0.0003002961,0.00007851137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008644303,"about_ca_system_score_gemma":0.0003390556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03983138,"about_ca_topic_score_gemma":0.02884267,"domain_scores_codex":[0.9998578,0.00003486065,0.00001344668,0.00004297735,0.0000334927,0.00001738397],"domain_scores_gemma":[0.9995351,0.0002018654,0.00008528319,0.0000233025,0.0001395486,0.00001491004],"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":[0.0001469749,0.00008888933,0.04281151,0.00003300326,0.0001074275,0.00004442858,0.00002371023,0.9255362,0.001605724,0.0001871623,0.0004127083,0.0290023],"study_design_scores_gemma":[0.000002413295,0.00001207379,0.006523571,0.000002016484,0.000005968977,0.000002115164,0.000006092268,0.9930223,0.0002602228,0.0001120897,0.0000484593,0.000002685543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548662,0.0002568699,0.04099899,0.0002453486,0.00004847958,0.00004053225,0.0005884038,0.0003521075,0.002603137],"genre_scores_gemma":[0.9964324,0.00005258035,0.002854503,0.00001370312,0.000009298417,0.00001233964,0.0002538458,0.000003808944,0.0003674607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03983138,"threshold_uncertainty_score":0.07919908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1010598464492268,"score_gpt":0.3101007969073739,"score_spread":0.2090409504581471,"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."}}