{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002024896,0.0001399231,0.0002831376,0.0002545239,0.00004675754,0.00002445457,0.00007174657,0.0001138785,0.00002764754],"category_scores_gemma":[0.0001033894,0.0001248593,0.00004429411,0.0005695244,0.00002966549,0.00009268913,0.00004678193,0.000159353,0.0001361614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006030344,"about_ca_system_score_gemma":0.00009057688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007418986,"about_ca_topic_score_gemma":0.0001591873,"domain_scores_codex":[0.9989119,0.00003529738,0.0003740528,0.0002631602,0.0001867346,0.0002288789],"domain_scores_gemma":[0.9995892,0.00004643917,0.0001181914,0.0001666403,0.00005952012,0.00002001408],"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":[0.00004330989,0.00004894238,0.01072666,0.00006112125,0.00001675377,0.00006379017,0.002462723,8.141283e-7,0.9855564,0.000004151797,0.0001081051,0.0009072294],"study_design_scores_gemma":[0.001254188,0.00006026676,0.04559362,0.0002330103,0.00002788223,0.00004716346,0.0002403941,0.0005986552,0.9512008,0.0002223653,0.0004031615,0.0001184867],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986249,0.00004511074,0.0003342959,0.0001920803,0.0001544578,0.0002054474,0.00003313463,0.0001898746,0.0002206699],"genre_scores_gemma":[0.9969048,7.952659e-7,0.002358936,0.0004730804,0.00009613568,0.000005991706,0.00005098271,0.00003737672,0.00007190541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03486697,"threshold_uncertainty_score":0.5091616,"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."}}