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Record W2332111793 · doi:10.1139/cjz-2013-0283

Anthropogenic food use and diet overlap between red foxes (<i>Vulpes</i><i>vulpes</i>) and arctic foxes (<i>Vulpes</i><i>lagopus</i>) in Prudhoe Bay, Alaska

2014· article· en· W2332111793 on OpenAlexvenueno aff
Garrett A. Savory, C Hunter, Matthew J. Wooller, Diane M. O’Brien

Bibliographic record

VenueCanadian Journal of Zoology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersOffice of Experimental Program to Stimulate Competitive ResearchNational Science Foundation
KeywordsVulpesLagopusBayArctic foxBiologyArcticEcologyPredationZoologyGeography

Abstract

fetched live from OpenAlex

Red foxes (Vulpes vulpes (L., 1758)) recently expanded into the oil fields at Prudhoe Bay, Alaska, USA, and we hypothesized that the availability of anthropogenic foods may contribute to their success and persistence there. This study assessed the importance of anthropogenic foods to the diets of red foxes and arctic foxes (Vulpes lagopus (L., 1758)), and competition for food resources between the two species in Prudhoe Bay. We used stable isotope analysis of fox tissues to infer diet during summer and winter for both red and arctic foxes, and lifetime diet for red fox. While the contribution of anthropogenic foods in late summer for both species’ diets was low (~10% to 15%), the contribution in late winter was higher and varied between species (red foxes = 49%; arctic foxes = 39%). Estimates of lifetime diet in red foxes suggest consistent use of anthropogenic foods. We found moderate overlap of fox diets, although red foxes appeared to be more specialized on lemmings, whereas arctic foxes had a more diverse diet. Availability and consumption of anthropogenic foods by red foxes, particularly in winter, may partially explain their year-round presence in Prudhoe Bay.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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.

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

Citations42
Published2014
Admission routes1
Has abstractyes

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