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Record W2382947628 · doi:10.35691/jbm.5102.0036

Status and Future Management of Grey Goral (Naemorhedus goral bedfordi) in Pakistan

2015· article· en· W2382947628 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Bioresource Management · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsNutrasource
Fundersnot available
KeywordsEndangered speciesPopulationThreatened speciesPredationHabitatBiologyPopulation bottleneckEcologyPopulation growthDemography

Abstract

fetched live from OpenAlex

Himalayan grey goral (HGG: Naemorhedus goral bedfordi) is endemic to Himalyas and regarded as Endangered/ Threatened. Study was designed to collect information on population biology, habitat, food and behaviour of population of HGG distributed in Pakistan, trying to understand its present status and conservational potentials. Our data suggest that the population, habitat and the species has sufficient potentials for its survival in the area, if protection from human predation is afforded to the species. HGG population is isolated into 7-8 subpopulations and is facing male-biased mortality, therefore is likely to face bottleneck effects and subsequent population crash ascribed to loss of males and genetic diversity. HGG population has a slow growth rate, attributable to internal species potentials and the natural predation of fawns/ sub-adults, which is difficult to be enhanced therefore range management strategy is suggested as management solution, with emphasis on protection from hunting, habitat management, mass awareness and supportive research. International cooperation is suggested as part of HGG population extends into Indian part of Himalayas, including Indian Kashmir.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.252
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it