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Contrasting the summer ecology of white-tailed deer inhabiting a forested and an agricultural landscape

2002· article· en· W2544931292 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEcoscience · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsCenter for Northern StudiesMinistère des Ressources naturelles et des ForêtsUniversité du Québec à Rimouski
Fundersnot available
KeywordsEcologyHabitatGeographyForageForesterHome rangeRange (aeronautics)AgroforestryForestryBiology

Abstract

fetched live from OpenAlex

: We compared habitat use, home range size, movements, and activity during summer between rural (12 animals km-2) and forest (<; 1 animal km-2) white-tailed deer populations, hypothesizing that competition for natural forage at high density would influence deer behaviour. Biomass of preferred forage at forester sites was 6 times greater in the forest than in the rural landscape. Forest deer avoided conifer and mixed stands, whereas rural deer tended to avoid stands of shade-tolerant hardwoods. Rural deer intensified their use of cultivated fields at night and ate a greater variety of native plants than forest conspecifics, including species rarely consumed by forest deer (e.g., ferns). Rural deer used smaller home ranges but moved at a greater rate than forest counterparts. Activity pattern of deer did not differ between the two landscapes, with peaks at dawn and dusk. Our results suggest that rural deer adapted to the rarity of natural forage by exploiting agricultural crops.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score1.000

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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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