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Record W1554649938 · doi:10.1002/jwmg.488

Factors influencing the reaction of mountain goats towards all‐terrain vehicles

2012· article· en· W1554649938 on OpenAlexafffundabout
Antoine St‐Louis, Sandra Hamel, Julien Mainguy, Steeve D. Côté

Bibliographic record

VenueJournal of Wildlife Management · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Conservation Association
KeywordsWildlifeDisturbance (geology)PopulationTerrainGeographyHabitatEcologyEnvironmental scienceDemographyBiology

Abstract

fetched live from OpenAlex

Abstract The increasing popularity of recreational activities in the wild has led to concerns about their potential impacts on wildlife. All‐terrain vehicles (ATVs) often bring people into wildlife habitats, where they may disturb animal populations. We assessed the influence of ATVs on the behavior of mountain goats ( Oreamnos americanus ) in a long‐term study population at Caw Ridge, Alberta, Canada. We used multinomial models containing environment‐, disturbance‐, and group‐related factors, to evaluate the response of mountain goats to the approach of ATVs. Goats were moderately to strongly disturbed by ATVs 44% of the time, and disturbance levels were mainly influenced by the direction and speed of the approaching vehicles. Environment‐ or group‐related factors (e.g., time of year, distance to escape terrain, group size or type) did not affect mountain goat responses to ATVs. Because goat reactions were influenced by disturbance‐level factors, we propose mitigating measures regarding the use of ATVs in the wild to minimize the disturbance to mountain goats, and potentially other alpine ungulates. © 2012 The Wildlife Society.

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 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 score0.011
Threshold uncertainty score0.279

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 communication0.0000.001
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 head0.026
GPT teacher head0.253
Teacher spread0.227 · 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 teacher head, 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

Citations22
Published2012
Admission routes3
Has abstractyes

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