doi:10.4061/2011/591980 Research Article Lesion Distribution and Epidemiology of Mycobacterium bovis in
Bibliographic record
Abstract
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Surveillance for Mycobacterium bovis in free-ranging elk (Cervus elaphus) and white-tailed deer (Odocoileus virginianus) from south-western Manitoba was carried out from 1997 to 2010 to describe the lesions, epidemiology, and geographic distribution of disease. Tissues were cultured from animals killed by hunters, culled for management, blood-tested, or found opportunistically. Period prevalence in elk was approximately six times higher than deer, suggesting a significant reservoir role for elk, but that infected deer may also be involved. Prevalence was consistently higher in elk compared to deer in a small core area and prevalence declines since 2003 are likely due to a combination of management factors instituted during that time. Older age classes and animals sampled from the core area were at significantly higher risk of being culture positive. Positive elk and deer were more likely to be found through blood testing, opportunistic surveillance, and culling compared to hunting. No non-lesioned, culture-positive elk were detected in this study compared to previous studies in red deer. 1.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.629 | 0.431 |
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".