{"id":"W4315487092","doi":"10.3390/microorganisms11010174","title":"Temporal Variation of SARS-CoV-2 Levels in Wastewater from a Meat Processing Plant","year":2023,"lang":"en","type":"article","venue":"Microorganisms","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hatch; Division of Chemical, Bioengineering, Environmental, and Transport Systems; U.S. Department of Agriculture; National Institute of Food and Agriculture; National Science Foundation","keywords":"Wastewater; Outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Environmental science; 2019-20 coronavirus outbreak; Sewage treatment; Fraction (chemistry); Meat packing industry; Waste management; Biology; Medicine; Environmental engineering; Virology; Infectious disease (medical specialty); Engineering; Food science; Chemistry; Pathology","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0001608618,0.0001579806,0.0002689825,0.0004773485,0.0004380074,0.0006418135,0.0001774204,0.0002948061,0.0007730357],"category_scores_gemma":[0.000494188,0.000100322,0.0002173381,0.0007666606,0.0002133535,0.000174072,0.0002465394,0.0002585523,0.0001627924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001189567,"about_ca_system_score_gemma":0.0007963618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1571496,"about_ca_topic_score_gemma":0.2148098,"domain_scores_codex":[0.9997315,0.00002796492,0.00001714665,0.00007822249,0.00008537709,0.00005978967],"domain_scores_gemma":[0.999534,0.00005526197,0.0001121605,0.00001615372,0.000234086,0.00004839287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005518339,0.0001099825,0.9367781,0.00008710338,0.00008049396,0.0004894599,0.001201085,0.0005021966,0.0487561,0.00005828891,0.0005438946,0.01084157],"study_design_scores_gemma":[0.000001738554,0.00009003498,0.994835,0.000007534532,0.00001833662,0.0001321124,0.0009826433,0.0004298096,0.002942895,0.00001561022,0.0005366401,0.000007612195],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979655,0.00007982838,0.0002273607,0.00003116135,0.000004197181,0.00001203477,0.0008954571,0.000009732223,0.0007748675],"genre_scores_gemma":[0.9981506,0.00007813703,0.0002401285,0.0000282638,0.000003031877,0.00001081815,0.0006934929,0.000003002259,0.0007925953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1571496,"threshold_uncertainty_score":0.3124698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07271092961152792,"score_gpt":0.3012391625477103,"score_spread":0.2285282329361824,"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."}}