A Transdisciplinary Approach to Brucella in Muskoxen of the Western Canadian Arctic 1989–2016
Bibliographic record
Abstract
Brucella serostatus was evaluated in 3189 muskoxen sampled between 1989 and 2016 from various locations of the Canadian Arctic archipelago and mainland, near the communities of Sachs Harbour and Ulukhaktok, Northwest Territories, and Cambridge Bay and Kugluktuk, Nunavut. Brucella antibodies were found only in muskoxen sampled around Cambridge Bay, both on southern Victoria Island and on the adjacent mainland (Kent Peninsula). Consistent with participatory epidemiology data documented from local harvesters describing increased Brucella-like syndromes (swollen joints and lameness) and a decreased proportion of juveniles, the apparent Brucella seroprevalence in the sampled muskoxen of the Cambridge Bay area increased from 0.9% (95% CI 0.3-2.1) in the period of 1989-2001 to 5.6% (95% CI 3.3-8.9) in 2010-2016. The zoonotic bacteria Brucella suis biovar 4 was also cultured from tissues of muskoxen sampled on Victoria Island near Ulukhaktok in 1996 (n = 1) and Cambridge Bay in 1998, 2014, and 2016 (n = 3). Overall, our data demonstrate that B. suis biovar 4 is found in muskoxen that are harvested for food and by guided hunts on Victoria Island and Kent Peninsula, adding an important public health dimension to this study. Robust participatory epidemiology data on muskox health and diseases greatly enhanced the interpretation of our Cambridge Bay data and, combined with the serological and microbiological data, provide compelling evidence that the prevalence of B. suis biovar 4 has increased in this area since the late 1990s. This study enhances the available knowledge on Brucella exposure and infection in muskoxen and provides an example of how scientific knowledge and local knowledge can work together to better understand disease status in wildlife.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".