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Record W2790615230 · doi:10.22621/cfn.v131i3.1822

Diet of Grey Wolves (Canis lupus) During Calving in a Moose– Caribou System in Northern Ontario

2018· article· en· W2790615230 on OpenAlexafffundvenueabout
Rob Found, Ashley McLaren, Arthur Rodgers, Brent R. Patterson

Bibliographic record

VenueThe Canadian Field-Naturalist · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistry of Natural Resources and Forestry
FundersCanadian Forest ServiceU.S. Forest ServiceOntario Ministry of Natural Resources and ForestryMinistry of Natural Resources
KeywordsWoodland caribouCanisPredationBeaverSnowshoe hareEcologyGray wolfUrsusGeographyBiologyZoologyPopulationDemography

Abstract

fetched live from OpenAlex

Grey Wolves (Canis lupus) are a leading proximate cause of declining populations of Woodland Caribou (Rangifer tarandus), a threatened species. Although predation on adult caribou has been well documented, less is known about predation on neonatal calves. We used scat analysis to examine the diet of wolves in an area of Ontario overlapping the receding southern limit of caribou occurrence. Wolves consumed mostly Moose (Alces americanus; 82.7%), followed by American Beaver (Castor canadensis; 10.9%), caribou (3.1%), and Snowshoe Hare (Lepus americanus; 1.5%). This low use of caribou is consistent with other evidence suggesting that caribou are a minor dietary component of wolves in this system; however, because most caribou consumption consists of calves, the impact on this slowly reproducing species may still be significant.

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)0.000
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 score0.016
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.192
Teacher spread0.184 · 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

Citations10
Published2018
Admission routes4
Has abstractyes

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