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Record W4224909248 · doi:10.24124/2022/59274

Behavioural, physiological, and movement relationships between barren-ground caribou and industrial infrastructure in the Northwest Territories

2022· dissertation· en· W4224909248 on OpenAlexaboutno aff
Angus Smith

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsForagingGeographyMovement (music)Physical geographyEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

I investigated the behavioural, physiological, and movement responses of barren-ground caribou to the Tibbitt to Contwoyto Winter Road in the central Northwest Territories. Previous research on the zone of influence around industrial infrastructure indicates that caribou avoid these industrial disturbances. This response implies changes in the behaviour, physiology, and movement of caribou as well. I used a multi-method approach to investigate these hypothesized changes for caribou adjacent to the road, employing behavioural observations, assessment of levels of fecal glucocorticoids, and GPS collar data. My results suggest that caribou change their behaviour and movement near the winter road. They engaged in more walking and less foraging near the road, though no relationship was found between the level of fecal glucocorticoids and proximity to the winter road. Using a novel estimation of traffic activity, I demonstrated that caribou crossing of the winter road was negatively correlated with the level of traffic. This barrier effect was not just related to the road’s right-of-way as caribou crossed roads when they were closed to traffic and the probability of selecting a crossing site was extremely low when normal levels of traffic occurred. My results provide new insights on the spatial, behavioural, and physiological responses of caribou when adjacent to industrial features. These findings can guide monitoring and mitigation of existing infrastructure and assist with the evaluation of impacts of proposed mines and roads.

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 score0.937
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.043
GPT teacher head0.262
Teacher spread0.219 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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