Multi-pathogen serological survey of migratory caribou herds: A snapshot in time
Bibliographic record
Abstract
Pathogens can impact host survival, fecundity, and population dynamics even when no obvious disease is observed. Few baseline data on pathogen prevalence and diversity of caribou are available, which hampers our ability to track changes over time and evaluate impacts on caribou health. Archived blood samples collected from ten migratory caribou herds in Canada and two in Greenland were used to test for exposure to pathogens that have the potential to effect population productivity, are zoonotic or are emerging. Relationships between seroprevalence and individual, population, and other health parameters were also examined. For adult caribou, the highest overall seroprevalence was for alphaherpesvirus (49%, n = 722), pestivirus (49%, n = 572) and Neospora caninum (27%, n = 452). Lower seroprevalence was found for parainfluenza virus type 3 (9%, n = 708), Brucella suis (2%, n = 758), and Toxoplasma gondii (2%, n = 706). No animal tested positive for antibodies against West Nile virus (n = 418) or bovine respiratory syncytial virus (n = 417). This extensive multi-pathogen survey of migratory caribou herds provides evidence that caribou are exposed to pathogens that may have impacts on herd health and revealed potential interactions between pathogens as well as geographical differences in pathogen exposure that could be linked to the bio-geographical history of caribou. Caribou are a keystone species and the socio-economic cornerstone of many indigenous cultures across the North. The results from this study highlight the urgent need for a better understanding of pathogen diversity and the impact of pathogens on caribou health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".