Reviving lost shadows: investigating the habitat ecology of the rediscovered hispid hare (<i>Caprolagus hispidus</i>) in Nepal
Bibliographic record
Abstract
) is one of the least studied mammal species. The recent rediscovery of hispid hare in Chitwan National Park (CNP) after three decades, necessitated urgent conservation measures. A detailed investigation into the species' ecology is imperative for developing evidence-based conservation strategies to support these efforts. The main objective of this study is to investigate the current distribution pattern and habitat preferences, offering vital insights for the effective preservation and management of the species and its habitat. Between 28 January and 13 February 2023, fifty-two surveys using strip transects were carried out in the potential areas. If any indirect signs of the presence of the hispid hare were identified, the corresponding value is coded as 1 "used plot". In contrast, a value of 0 was assigned if there is an absence of any indirect signs "habitat availability plot". Nine habitat predictors (habitat type, ground cover, distance to water source, distance to roads/path/firelines, ground condition, dominant plant species, presence/absence of (anthropogenic disturbance, predators, and invasive species), were measured from both plot types ("used plot" and "habitat availability plot"). Our research indicates a clumped distribution pattern within the CNP, with the Sukhibhar grassland identified as a key hotspot. Our study reveals the hispid hare's adaptability to diverse grassland conditions, favoring both tall and short grasslands. It is essential to integrate the species' preference for various grassland habitats and critical water sources to enhance conservation strategies. This requires a comprehensive grassland management plan for Chitwan National Park that preserves habitat diversity, safeguards key water sources, and adapts to evolving environmental conditions.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".