{"id":"W4224060503","doi":"10.1101/2022.04.12.22273761","title":"Multiplex RT-qPCR assay (N200) to detect and estimate prevalence of multiple SARS-CoV-2 Variants of Concern in wastewater","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Saskatchewan; Public Health Agency of Canada; University of Toronto; University of Waterloo","funders":"Global Water Futures; Canada Research Chairs; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Ministère de l’Environnement, de la Protection de la nature et des Parcs; Public Health Agency of Canada","keywords":"Multiplex; Wastewater; Amplicon; Biology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Real-time polymerase chain reaction; Virology; Molecular biology; Coronavirus disease 2019 (COVID-19); Polymerase chain reaction; Gene; Genetics; Medicine; Environmental science; Environmental engineering; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001021688,0.001176166,0.0005292552,0.000974268,0.0003938556,0.0004827963,0.0006295951,0.0007221186,0.001651014],"category_scores_gemma":[0.0009509968,0.0005353321,0.0004548209,0.0007761728,0.0003984428,0.0002682147,0.0003758049,0.0004536032,0.0006383863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001250595,"about_ca_system_score_gemma":0.001178687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006848118,"about_ca_topic_score_gemma":0.02539894,"domain_scores_codex":[0.9979151,0.0002356207,0.0001384271,0.0006753351,0.0008973871,0.0001380959],"domain_scores_gemma":[0.9994469,0.0001093966,0.000118939,0.00005710218,0.0002299406,0.00003767126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001463642,0.0001337473,0.00833888,0.00007567317,0.00001908592,0.00003481777,0.00009658901,0.0005069589,0.9851908,0.00009833996,0.0002827418,0.005075921],"study_design_scores_gemma":[0.00004881651,0.0009169543,0.04178143,0.00004730922,0.00007349867,0.0003024766,0.0001424665,0.01925881,0.9282823,0.0001285353,0.008962173,0.00005525614],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8204582,0.0007617176,0.1581192,0.0001952385,0.0001911377,0.002100219,0.01016859,0.001690251,0.006315457],"genre_scores_gemma":[0.655942,0.0007038713,0.3073803,0.0005399021,0.00005037283,0.003756021,0.0131997,0.000120774,0.01830711],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006848118,"threshold_uncertainty_score":0.01361656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07474096794560371,"score_gpt":0.3410993651243691,"score_spread":0.2663583971787654,"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."}}