Poaching, recruitment and conservation of Punjab urial Ovis vignei punjabiensis
Bibliographic record
Abstract
Poaching can accelerate extinction processes, particularly when driven by commercial gain. We studied Punjab urial Ovis vignei punjabiensis, an endangered wild sheep, in two areas of the Salt Range in Pakistan, with contrasting human population densities and management regimes. In the Eastern Salt Range (ESR), humans live adjacent to urial habitat and enforcement of antipoaching regulations is lax. In the Kalabagh Game Reserve (KGR), human population density is low and regulations are strictly enforced. In ESR, about a quarter of the lamb crop was removed by poachers, and all rams > 6 years old were eliminated by illegal shooting. In KGR, < 5% of lambs were removed and about 34% of adult rams were ≥ 6 years old. Yearly recruitment was only four yearling females per 100 ewes in ESR, compared to about 13 yearling females per 100 ewes in KGR. Recruitment was insufficient to maintain the population in ESR. Poaching of newborn lambs to be kept as pets appears to be the greatest short-term threat to Punjab urial, recently exacerbated by the granting of licences to legally possess pet urial. Over the long term, the increasing human population in the area presents additional challenges.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".