Co‐circulation of five species of dog parvoviruses and canine adenovirus type 1 among gray wolves (<i>Canis lupus</i>) in northern Canada
Bibliographic record
Abstract
Several viruses can infect wild carnivores but their impact on wildlife health is poorly understood. We investigated the presence, diversity and distribution of various DNA viruses in 303 wolves inhabiting a vast area of the Northwest Territories, Canada, over a period of 13 years. We found evidence for the presence of canine bufavirus (CBuV, 42.6%), canine parvovirus 2 (CPV-2, 34.0%), canine bocavirus 2 (CBoV-2, 5.0%), cachavirus (CachaV-1, 2.6%), canine adenovirus 1 (CAdV-1, 1%) and minute virus of canines (MVC, 0.3%). To our knowledge, this is the first detection of CBoV-2, MVC and CachV-1 in wild animals. We also demonstrate that CBuV and CachaV-1 were already circulating among wild animals at least 11 and 10 years, respectively, before their discoveries. Although CBuV prevalence was higher, CPV-2 was the most prevalent virus among juveniles, while CBuV infection was associated with poor nutrition conditions. Even if its prevalence was low, CachaV-1 had the highest multiple infection rate (87.5%). CadV-1 and MVC sequences were highly identical to reference strains, but we observed a high diversity among the other viruses and detected three new variants. One CPV-2 variant and one CBuV variant were endemic since the beginning of the 2000s in the entire investigated region, whereas one CBuV variant and two CBoV-2 variants were found in a more restricted area over multiple years and CachaV-1 was found only in one region. Two CPV-2 variants and one CachaV-1 variant were observed only once, indicating sporadic introductions or limited circulation. Different patterns of endemicity might indicate that viruses were introduced in the wolf population at different timepoints and that mixing between wolf packs may not be constant. Different epidemiological behaviors depend on viral factors like infectivity, transmission routes, pathogenicity and tissue-tropism, and on host factors like proximity to densely populated areas, carnivory and pack density and mixing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".