{"id":"W4293162924","doi":"10.1016/j.scitotenv.2022.158266","title":"Whole genome sequencing of SARS-CoV-2 from wastewater links to individual cases in catchments","year":2022,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Wastewater; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Transmission (telecommunications); Coronavirus disease 2019 (COVID-19); Outbreak; Quarantine; Genome; Sewage treatment; Whole genome sequencing; Biology; 2019-20 coronavirus outbreak; Quarter (Canadian coin); Pandemic; Metagenomics; Geography; Environmental health; Environmental science; Ecology; Medicine; Virology; Infectious disease (medical specialty); Disease; Genetics; Environmental engineering; Engineering; Telecommunications; Archaeology; Gene; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004445994,0.0003172192,0.0004294643,0.001298947,0.0007473899,0.001224184,0.0003030326,0.0008036171,0.002202781],"category_scores_gemma":[0.001852438,0.000280535,0.0005394149,0.002052258,0.0003914258,0.0002956066,0.0009963214,0.0005579652,0.000354512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006948552,"about_ca_system_score_gemma":0.000784823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03336836,"about_ca_topic_score_gemma":0.03949496,"domain_scores_codex":[0.9992106,0.0001294252,0.00005209994,0.0002619121,0.0001295437,0.0002163603],"domain_scores_gemma":[0.9994784,0.0001163396,0.0001171476,0.00003929849,0.0001532473,0.00009558813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003877319,0.00008053327,0.964453,0.00009285124,0.0002323967,0.001046471,0.001629154,0.000472467,0.0183761,0.0002031154,0.002540582,0.01048566],"study_design_scores_gemma":[0.00002165214,0.00005867721,0.9936873,0.00003313821,0.00009202311,0.0005834312,0.001705823,0.0004054485,0.0006642133,0.0002354325,0.002503738,0.000009208716],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995245,0.0001954586,0.0005058229,0.000197282,0.00001174462,0.000025759,0.003057061,0.00001719597,0.0007447001],"genre_scores_gemma":[0.9947583,0.0001896491,0.0004876633,0.0002309919,0.00001354001,0.00002298715,0.003542563,0.00002694954,0.0007273771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03336836,"threshold_uncertainty_score":0.06634825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05570327394757756,"score_gpt":0.276501486616319,"score_spread":0.2207982126687414,"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."}}