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Record W1578680105 · doi:10.22621/cfn.v123i2.931

Declines of Bighorn Sheep, <em>Ovis canadensis</em>, on Deteriorating Winter Range in Jasper National Park, Alberta, 1981-2010

2009· article· en· W1578680105 on OpenAlexfundvenueaboutno aff
Dick Dekker

Bibliographic record

VenueThe Canadian Field-Naturalist · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsnot available
FundersParks CanadaWorld Wildlife Fund
KeywordsOvis canadensisOvisNational parkAnimal scienceGeographyRange (aeronautics)LivestockBiologyEcologyForestryDemographyPopulation

Abstract

fetched live from OpenAlex

Bighorn Sheep (Ovis canadensis) wintering in the lower Athabasca River valley of Jasper National Park, Alberta, were monitored from 1981 to 2010 by recording maximum band sizes per annum on two traditional but separate sheep ranges. In study area #1, the ram band declined significantly from a 20-year mean of 18 in the period 1981-2001 to a 5-year mean of 11 in the period 2001-2006, with a slight recovery in 2006-2010. Ewes in area #1 dwindled from a mean of 20 in the period 1981-1995 to zero in the period 1995-2010. In area #2, the ewe band dropped significantly from a mean of 40 in the period 1981-2001 to 24 in the period 2001-2010. The declines in area #1 coincided with an invasion of Russian Thistle (Salsola kali). Range conditions in area #2 deteriorated following four years with lower than average annual precipitation. The mean lamb:ewe ratio in area #2, pooled for 29 years, was 22:100 (n = 646). The sheep were protected from hunting, but were subject to a full range of indigenous carnivores. However, predation did not appear to be the primary cause of the declines, nor was competition for forage with American Elk (Cervus elaphus).

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.242
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.224
Teacher spread0.211 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2009
Admission routes3
Has abstractyes

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