Serosurveillance for Severe Acute Respiratory Syndrome Coronavirus 2 Antibody in Feral Swine and White-Tailed Deer in Texas
Bibliographic record
Abstract
Background: Serological evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been reported in white-tailed deer (WTD) in the United States and Canada. Even though WTD are susceptible to SARS-CoV-2 infection, there is no evidence of infection by this virus in other mammalian species that might interact with WTD in nature. Similar to WTD, feral swine are widely distributed and generally occupy the same range as WTD in Texas. The objective of this study was to determine the prevalence of SARS-CoV-2 neutralizing antibody in WTD during 2020 and 2021 and determine the prevalence of SARS-CoV-2 neutralizing antibody in feral swine during 2018 (prepandemic period) and from March 2020 to February 2021 (pandemic period) in Travis County, Texas. Materials and Methods: Sera samples were collected from hunter-killed WTD and feral swine during the prepandemic and pandemic period and tested for SARS-CoV-2 antibody by a plaque reduction neutralization assay in Vero cells. Results: SARS-CoV-2 antibody was not detected in any of the 166 feral swine sera samples, including 24 samples collected during the prepandemic and 142 samples collected during the pandemic period. Furthermore, SARS-CoV-2 antibody was not detected in the 115 WTD samples collected during late 2020, but antibody was detected in WTD in early 2021. Conclusions: The results indicated that SARS-CoV-2 infection of WTD occurred during early 2021 in Travis County, Texas, but serological evidence of SARS-CoV-2 infection was not detected in the feral swine samples collected from the same locality and during the same time period of the collection of WTD samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".