{"id":"W4293249179","doi":"10.1021/acsestwater.2c00058","title":"Quantitative Trend Analysis of SARS-CoV-2 RNA in Municipal Wastewater Exemplified with Sewershed-Specific COVID-19 Clinical Case Counts","year":2022,"lang":"en","type":"article","venue":"ACS ES&T Water","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; Toronto Public Health; Public Health Agency of Canada; Canada Research Chairs; Ministry of the Environment, Conservation and Parks","funders":"","keywords":"Wastewater; Sewage treatment; Coronavirus disease 2019 (COVID-19); Normalization (sociology); Environmental science; Environmental health; Medicine; Environmental engineering; Infectious disease (medical specialty); Pathology","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":[0.001116258,0.0002881946,0.000247825,0.001554155,0.0002511018,0.0006970392,0.0002414007,0.0002654124,0.0009556928],"category_scores_gemma":[0.001788752,0.0001481458,0.0002491125,0.00183622,0.0002170629,0.0002811516,0.0002725207,0.0002925458,0.0002300551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007794281,"about_ca_system_score_gemma":0.0008752217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02234307,"about_ca_topic_score_gemma":0.04530732,"domain_scores_codex":[0.999146,0.0001133055,0.00006389924,0.000206586,0.0003897805,0.00008042232],"domain_scores_gemma":[0.9988222,0.0002449775,0.0003148643,0.0000893281,0.000489287,0.00003940745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005368558,0.0002142655,0.5699373,0.0002443689,0.0001746021,0.0002026601,0.001020459,0.005174194,0.3041123,0.0009533091,0.001236547,0.1161931],"study_design_scores_gemma":[0.00002351334,0.000826944,0.7754221,0.00003488347,0.0001582665,0.0005063151,0.0009982848,0.06832696,0.1436651,0.0009598245,0.008998403,0.000079261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9028499,0.000376754,0.08573788,0.0001689334,0.00003137083,0.0001753376,0.006289352,0.0006813101,0.003689263],"genre_scores_gemma":[0.9477692,0.0001920623,0.04758912,0.00005079509,0.00001551002,0.0001366083,0.002237702,0.00004093741,0.001968079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02234307,"threshold_uncertainty_score":0.04442602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1817732115898527,"score_gpt":0.4059824735997683,"score_spread":0.2242092620099156,"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."}}