{"id":"W3209981321","doi":"10.1016/j.scitotenv.2021.151283","title":"RT-qPCR detection of SARS-CoV-2 mutations S 69–70 del, S N501Y and N D3L associated with variants of concern in Canadian wastewater samples","year":2021,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; University of Manitoba; Public Health Agency of Canada","funders":"Public Health Agency of Canada","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Wastewater; Coronavirus disease 2019 (COVID-19); Population; Environmental health; 2019-20 coronavirus outbreak; Biology; Medicine; Virology; Environmental engineering; Environmental science; Outbreak; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.000497714,0.00007622526,0.0001548168,0.00008440751,0.0001236441,0.000007799717,0.0001019554,0.00003061972,0.00001466789],"category_scores_gemma":[0.0003068033,0.00004642844,0.00002985968,0.0003774867,0.0008230524,0.00006743343,0.00006556243,0.00009731214,0.000001631476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001795665,"about_ca_system_score_gemma":0.0002043871,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02774318,"about_ca_topic_score_gemma":0.008815564,"domain_scores_codex":[0.9990538,0.00006322293,0.000210878,0.0001624028,0.0003198237,0.000189897],"domain_scores_gemma":[0.9994774,0.00007361396,0.0001479559,0.0002327251,0.00003349019,0.00003480471],"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":[0.00001475243,0.00003775371,0.00152301,0.000007695711,0.0000176619,0.000002382591,0.0006833024,0.0005175575,0.9968691,0.00001760629,6.206712e-7,0.0003085392],"study_design_scores_gemma":[0.0003955635,0.00009895072,0.1604061,0.00008424597,0.0000406207,0.00004287444,0.0004453265,0.002344709,0.8360243,0.00006915347,0.000005127464,0.00004299637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990501,0.00004144196,0.00001808905,0.0002907445,0.00005268115,0.0001791281,0.00001212522,0.00000415067,0.0003515425],"genre_scores_gemma":[0.9997568,0.000003650727,0.0001229459,0.00004686909,0.000005263561,0.000004634262,7.366149e-7,0.000006256686,0.00005287427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1608448,"threshold_uncertainty_score":0.9787312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03900087960047639,"score_gpt":0.2556357191398778,"score_spread":0.2166348395394014,"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."}}