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Record W4400448351 · doi:10.1080/1357650x.2024.2374765

Footedness in merlins: Raptors perching in a cold climate

2024· article· en· W4400448351 on OpenAlexafffundabout
Ian G. Warkentin

Bibliographic record

VenueLaterality Asymmetries of Body Brain and Cognition · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of SaskatchewanAmerican Museum of Natural History
KeywordsEnvironmental scienceGeography

Abstract

fetched live from OpenAlex

Perching or standing on one foot is commonly reported in birds but the level of consistency in using one foot over the other has been less-well documented in most species, particularly birds of prey. For birds experiencing colder temperatures, unipedal perching has been attributed to limiting heat loss through unfeathered legs and feet; individuals should spend longer periods of time perched on one foot as temperatures decrease. Using radio tracking, I collected 486 hours of observations on nine overwintering, free-living merlins (Falco columbarius) in Saskatoon, Canada. Five merlins displayed clear preferences to perch on one foot, however the direction of preference was not consistent and four birds were ambidextrous. There was a curvilinear response in the proportion of time spent in unipedal posture versus temperature, with a peak of ∼22% of the time at moderate temperatures (−10 to −19°C), but lower values at warmer and colder temperatures; the main effect of the squared term for temperature was highly influential while individual foot preference had no impact on the use of unipedal perching. Although preferential use of one foot for perching was displayed by some individuals, thermoregulation may not be the primary driver of this behaviour at colder temperatures.

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 score0.022
Threshold uncertainty score0.357

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)0.0000.000

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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