{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001323705,0.0004124477,0.0009902826,0.00052818,0.000054861,0.0000179992,0.0003295481,0.0002561973,0.00009546964],"category_scores_gemma":[0.002968335,0.0003943984,0.0001569294,0.0003841661,0.0001528754,0.00005970182,0.0009249082,0.0008209323,0.00001157383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001266721,"about_ca_system_score_gemma":0.0001647918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001147572,"about_ca_topic_score_gemma":0.0002195126,"domain_scores_codex":[0.9968901,0.0002965511,0.001009187,0.0008403394,0.0005443867,0.0004194339],"domain_scores_gemma":[0.9979122,0.000519489,0.0004892937,0.0008165768,0.0001782003,0.00008428194],"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":[0.0002859239,0.00007713596,0.2617067,0.001930324,0.0000669564,0.00008573295,0.0008393729,0.000197075,0.7324025,0.000001575826,0.00001791237,0.002388808],"study_design_scores_gemma":[0.001946043,0.0002727661,0.1743183,0.001190813,0.000118902,0.00006790198,0.00006094897,0.01171099,0.8096728,0.00007347561,0.000266042,0.0003009989],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965407,0.0003939132,0.0005346565,0.00007683523,0.000513437,0.001273469,0.0001247298,0.0001018261,0.0004403827],"genre_scores_gemma":[0.9902213,0.0000297072,0.009134502,0.000222883,0.00005928267,0.0001505624,0.000009219147,0.00007353719,0.000099054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08738834,"threshold_uncertainty_score":0.9998508,"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."}}