Prevalence of Antibodies to<i>Leptospira</i>in Wild Mammals Trapped on Livestock Farms in Ontario, Canada
Bibliographic record
Abstract
To determine the prevalence and diversity of Leptospira serogroups circulating in wildlife on farms in Ontario, we tested samples from 51 raccoons (Procyon lotor), seven skunks (Mephitis mephitis), four rats (Rattus norvegicus), and three opossums (Didelphis virginiana) that were trapped on 27 livestock (swine [Sus scrofa], cattle [Bos taurus]) farms in 2010. Seventeen of 51 raccoons (33%; 95% confidence interval [CI], 21-48%) sampled were positive for at least one Leptospira serogroup using the microscopic agglutination test. None of the other 14 animals had detectable Leptospira antibodies. On swine farms, 13 of 30 raccoons (43%; 95% CI, 27-61%) were antibody positive, and on cattle farms, four of 21 raccoons (19%; 95% CI, 8-40%) were positive. Leptospira antibody prevalence in raccoons did not differ between swine and cattle farms. Raccoons were positive to serovars representative of serogroups Grippotyphosa, Australis, Icterohaemorrhagiae, and Pomona and were negative to serovars of serogroups Autumnalis, Canicola, and Sejroe. The prevalence of Leptospira antibodies in raccoons in this study is similar to what has been reported previously; however, the diversity of serogroups was higher in this study than what has been reported in raccoons from an urban area of Ontario, Canada. Understanding the prevalence and distribution of Leptospira serogroups in wildlife in Ontario, Canada, is important for the development and maintenance of appropriate disease management strategies in humans, livestock, and companion animals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".