{"id":"W2225587141","doi":"10.1016/j.watres.2015.12.033","title":"The effects of combined sewer overflow events on riverine sources of drinking water","year":2016,"lang":"en","type":"article","venue":"Water Research","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Safe Engineering Services & Technologies (Canada); Natural Sciences and Engineering Research Council","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Snowmelt; Water quality; Environmental science; Precipitation; Hydrology (agriculture); Animal science; Snow; Environmental chemistry; Toxicology; Chemistry; Meteorology; Ecology; Geography; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0005324818,0.000245333,0.0002703242,0.0005339478,0.0005228741,0.001178079,0.0003058049,0.0005608321,0.004409647],"category_scores_gemma":[0.002334334,0.0001819423,0.000579517,0.0005482652,0.0003725502,0.0008312822,0.000915818,0.0004322456,0.0003341104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008730075,"about_ca_system_score_gemma":0.0005385225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01477083,"about_ca_topic_score_gemma":0.04126121,"domain_scores_codex":[0.9995263,0.0001698018,0.00002991629,0.00007137679,0.0001034984,0.00009910263],"domain_scores_gemma":[0.99704,0.001469382,0.0005374968,0.0001185239,0.0004641782,0.0003705418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01508497,0.001768276,0.8780288,0.0001759231,0.0007760315,0.001168576,0.0009342342,0.007038902,0.03631905,0.0004503784,0.001533968,0.05672089],"study_design_scores_gemma":[0.00006128458,0.001452875,0.9896611,0.00001053974,0.0001744153,0.0001016432,0.001140248,0.001930291,0.004666544,0.0001334111,0.0006531694,0.00001447857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983786,0.00004908905,0.00004961174,0.00003900284,0.00000612658,0.000006472667,0.0001876478,0.000003931742,0.001279439],"genre_scores_gemma":[0.998817,0.00006884409,0.00008001018,0.00001921032,0.00001006178,0.000004849705,0.0001551107,0.0000038825,0.0008409321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01477083,"threshold_uncertainty_score":0.02936971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02117759054649935,"score_gpt":0.2705688060592664,"score_spread":0.2493912155127671,"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."}}