MétaCan
Menu
← Back to cohort

How anthropogenic food sources and individual morphology inform wild turkey (Meleagris gallopavo) utilization distributions

2025· preprint· en· W4408302955 on OpenAlexafffundabout
Jennifer E. Baici, Jeff Bowman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsMinistry of Natural Resources and ForestryTrent University
FundersNatural Sciences and Engineering Research Council of CanadaTrent UniversityOntario Federation of Anglers and Hunters
KeywordsMeleagris gallopavoGeographyEcologyEnvironmental scienceAgroforestryBiologyZoology

Abstract

fetched live from OpenAlex

Many animals exploit anthropogenic food sources, like agricultural crops and bird feeders, and it is likely that the distribution of these resources can determine the size and composition of species’ home ranges. Wild turkeys (Meleagris gallopavo) use anthropogenic food sources across their range, particularly during the winter. As such, access to anthropogenic food sources may shape their seasonal movement patterns. We estimated home range size and core use areas for 65 wild turkeys in south-central Ontario from 2017 to 2019. We used satellite and aerial imagery to evaluate the composition of anthropogenic food sources within turkey utilization distributions (UDs) and found that, for females during the summer, crop was positively associated with home range size, whereas livestock exhibited a strong negative relationship. For males, the opposite relationships were detected with crop and livestock, and pasture was also a significant predictor of space use. Understanding the anthropogenic factors that affect wild turkey home range size and composition is important for making informed management decisions for the

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)0.001
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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.062
GPT teacher head0.259
Teacher spread0.196 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same topicAnimal Nutrition and Physiology→French-language works237,207→