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Record W4210418582 · doi:10.1038/s41598-022-05516-0

Egg-laying increases body temperature to an annual maximum in a wild bird

2022· article· en· W4210418582 on OpenAlexafffund
Magella Guillemette, David Pelletier

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsCégep de RimouskiUniversité du Québec à Rimouski
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEiderPredationBiologyAvian clutch sizeReproductionThermoregulationHabitatEcologyZoologyLayingAnimal science

Abstract

fetched live from OpenAlex

Most birds, unlike reptiles, lay eggs successively to form a full clutch. During egg-laying, birds are highly secretive and prone to disturbance and predation. Using multisensor data loggers, we show that average daily body temperature during egg-laying is significantly increased (1 °C) in wild eider ducks (Somateria mollissima). Strikingly, this increase corresponds to the annual maximum body temperature (40.7 °C), representing a severe annual thermogenic challenge. This egg-laying-induced rise in body temperature may prove to be a common feature of wild birds and could be caused by habitat-related thermoregulatory adjustments and hormonal modulation of reproduction. We conclude our findings with new perspectives of the benefits of high body temperature associated with egg-laying of birds and the potential effect of heat stress that may occur with the future advent of heatwaves.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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

Citations11
Published2022
Admission routes2
Has abstractyes

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