Assessing the health-fitness dynamics of endangered mountain caribou and the influence of maternal penning
Bibliographic record
Abstract
The health of wildlife plays a crucial role in population demography by connecting habitat and physiology. Southern mountain caribou, a population of woodland caribou ( Rangifer tarandus caribou (Gmelin, 1978)) found in the mountains of southwest Canada, are facing significant threats. We evaluated the health of the Klinse-Za subpopulation within the central group of southern mountain caribou, which is part of an Indigenous-led conservation initiative aimed at enhancing caribou population growth through seasonal maternal penning. We collected health metrics from 46 female Klinse-Za caribou between 2014 and 2021. The health metrics included trace minerals, cortisol, biomarkers for inflammation, and pathogen prevalence. We compared these health metrics between penned and non-penned animals, reproductive and non-reproductive females, and nearby subpopulations. We provide correlative evidence linking reproductive success to trace nutrients but find no evidence for relationships with stress, exposure to pathogens, or biomarkers of inflammation. Based on the health metrics considered, Klinse-Za caribou were generally healthy relative to neighboring subpopulations and repeat capture for penning did not appear to create accumulated health issues. Penned caribou had lower fecal cortisol levels and inflammation markers compared to free-ranging animals. This work provides a baseline assessment of southern mountain caribou health and provides guidance on maternal penning activities in support of caribou recovery.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".