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Record W2131688516 · doi:10.2193/2006-056

Winter Forage Selection in White‐Tailed Deer at High Density: Balsam Fir is the Best of a Bad Choice

2007· article· en· W2131688516 on OpenAlexafffundabout
Daniel G. Sauvé, Steeve D. Côté

Bibliographic record

VenueJournal of Wildlife Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsNatural Sciences and Engineering Research Council of Canada
FundersUniversité Laval
KeywordsBalsamAbies balsameaOdocoileusForageBiologyWhite (mutation)ForestryBotanyEcologyGeography

Abstract

fetched live from OpenAlex

Abstract: We assessed winter forage selection by white‐tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada, using cafeteria‐feeding trials. Winter habitat on Anticosti is degraded and free‐ranging deer at high densities consume 70% balsam fir (Abies balsamea) and 20% white spruce (Picea glauca) , even though spruce is much more available than fir. Deer ate 89.9% balsam fir and 10.1% white spruce when the availability of both trees was equal. Deer did not eat shredded twigs more than intact twigs. Fiber content and condensed tannins were greater in white spruce than in balsam fir. Deer preference for fir was not based on texture but, more likely, on plant constituents, so we concluded that deer will nearly eliminate fir before they use any significant amount of white spruce. Management actions, therefore, need to be undertaken to enhance balsam fir regeneration.

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 score0.021
Threshold uncertainty score0.943

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 communication0.0000.000
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 head0.227
Teacher spread0.218 · 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

Citations62
Published2007
Admission routes3
Has abstractyes

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