{"id":"W2528118042","doi":"10.1016/j.advwatres.2016.10.001","title":"Modelling the impacts of global change on concentrations of Escherichia coli in an urban river","year":2016,"lang":"en","type":"article","venue":"Advances in Water Resources","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Université de Sherbrooke; Polytechnique Montréal","funders":"","keywords":"Environmental science; Climate change; Combined sewer; Water quality; Population; Precipitation; Current (fluid); Hydrology (agriculture); Climate model; Environmental engineering; Water resource management; Geography; Meteorology; Ecology; Surface runoff; Stormwater; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000482421,0.0006639324,0.0005598603,0.000448281,0.0005811658,0.001356373,0.0009701049,0.00263448,0.002556057],"category_scores_gemma":[0.001577886,0.000610574,0.001087863,0.0007793,0.001015139,0.00108428,0.0007085091,0.001165289,0.0001772214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002436949,"about_ca_system_score_gemma":0.001615808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1226119,"about_ca_topic_score_gemma":0.07589889,"domain_scores_codex":[0.9997754,0.00005330319,0.00001180573,0.00005253498,0.00002306403,0.0000839501],"domain_scores_gemma":[0.9991884,0.000554429,0.00006215494,0.00003455559,0.00008904337,0.00007132789],"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":[0.00004237799,0.00005805757,0.004369277,0.00000910783,0.00001390449,0.00003889461,0.00001773798,0.994093,0.0003037257,0.000405762,0.00009430245,0.0005539023],"study_design_scores_gemma":[0.00002611877,0.00005726406,0.001850958,0.000002212807,0.0000132171,0.000006826646,0.00008680547,0.9970482,0.0003132676,0.0003979668,0.000187056,0.00001018593],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931752,0.00005484802,0.002439963,0.0003005098,0.00002441906,0.00001794429,0.0003576777,0.00004219657,0.003587263],"genre_scores_gemma":[0.9969749,0.0000670282,0.0009594234,0.00004026567,0.00000582117,0.00001568078,0.0001995746,0.00001339253,0.001723869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1226119,"threshold_uncertainty_score":0.2437965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078283907864534,"score_gpt":0.2469834759105922,"score_spread":0.2262006368319469,"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."}}