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Record W4405220688 · doi:10.1098/rsbl.2024.0365

Exploring sources of (co-)variation in timing and total daily feeder visits in a wild population of black-capped chickadees

2024· article· en· W4405220688 on OpenAlexafffund
Nathan L. Hobbs, Deborah M. Hawkshaw, Jan J. Wijmenga, Kimberley J. Mathot

Bibliographic record

VenueBiology Letters · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of Alberta
KeywordsForagingBiologyVariation (astronomy)PopulationEcologyZoologyDemography

Abstract

fetched live from OpenAlex

The timing and amount of foraging in birds are shaped by many of the same extrinsic factors, including temperature and daylength, as well as intrinsic factors, such as sex and age. Here, we investigate co-variation between these traits. We observed a population of 143 individually marked black-capped chickadees ( Poecile atricapillus ) over a 90 day period during the winter. For each day, we recorded the time an individual began and ended feeder use relative to sunrise/sunset, and the total number of feeder visits. Within-individuals, both earlier first feeder visit and later last feeder visit were associated with higher total daily feeder visits but lower feeding rates. Individuals also differed consistently in the timing of first and last feeder visits, and individuals that consistently started feeder use earlier in the day ended feeder use later and had higher total daily feeder visits compared with those that started later, but had no difference in feeding rate. Our study demonstrates that variation in the timing of foraging can have important consequences for energy acquisition at both the within- and among-individual levels.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.165

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)0.0000.000

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 head0.065
GPT teacher head0.258
Teacher spread0.193 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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