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Record W1862002066 · doi:10.1139/z2012-003

Space use and territoriality in swift foxes (<i>Vulpes velox</i>) in northeastern Colorado

2012· article· en· W1862002066 on OpenAlexvenueno aff
Amariah A. Lebsock, Christopher L. Burdett, Safi K. Darden, Torben Dabelsteen, Michael F. Antolin, Kevin R. Crooks

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsVulpesTerritorialityHome rangeBiological dispersalBiologyEcologyRange (aeronautics)PhilopatrySeasonal breederCarnivorePopulationGeographyDemographyHabitatPredation

Abstract

fetched live from OpenAlex

Space use is a fundamental characteristic that informs our knowledge of social relationships and the degree to which individuals are territorial. Until recently, relatively little was known about the spatial ecology and social organization of swift foxes ( Vulpes velox (Say, 1823)). We investigated space use of swift foxes on shortgrass prairie in northeastern Colorado. Our first objective was to evaluate sizes of seasonal and annual home ranges and core areas of 13 radio-collared swift foxes monitored continuously for 2 years. Our second objective was to compare home-range and core-area overlap of breeding pairs to that of neighboring foxes, including male–male, female–female, and nonbreeding female–male dyads. Home-range size in our study population was among the smallest previously reported for swift foxes. Males tended to have slightly larger home ranges and core areas than females, and home-range size was significantly larger in the breeding season than in both the pup-rearing and the dispersal seasons; sizes of core areas did not differ seasonally. Spatial overlap between breeding pairs was substantial, whereas spatial overlap between neighbors, particularly males, was low, suggesting territoriality.

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 score0.152
Threshold uncertainty score0.301

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 communication0.0000.000
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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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