Pre‐Monsoon Habitat Preference and Spatial Overlap Between Blue Sheep (<i>Pseudois nayaur</i>) and Livestock in Dhorpatan Hunting Reserve, Nepal
Bibliographic record
Abstract
ABSTRACT Blue sheep are crucial to the Himalayan high‐altitude ecosystems, but their habitat preferences are not well understood. Hence, this study investigated its pre‐monsoon habitat preference and spatial overlap with livestock in Dhorpatan Hunting Reserve, Nepal. Altogether, 126 plots were laid to sample the signs of blue sheep, vegetation, and habitat parameters. The species was found at elevations of 3651–4348 m, with a preference for sub‐alpine and alpine grasslands (3800–4200 meters) on south‐facing slopes of 10°–30°, within 300 m of water bodies. It favored areas with crown coverage of < 25% and ground coverage of > 50%. Preferred vegetation included shrubs like Rhododendron lepidotum and grasses from Cyperaceae, such as Kobresia and Carex species. There was a significant habitat overlap between blue sheep and livestock, along with the major threats including grazing, fire, poaching, snaring, and human interference. Management plans should address these issues to sustain the species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".