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Record W2117153049 · doi:10.1242/jeb.01397

Energetics of a long-distance migrant shorebird (<i>Philomachus pugnax</i>) during cold exposure and running

2005· article· en· W2117153049 on OpenAlexaff
Eric Vaillancourt, Sophie Martine Prud’homme, François Haman, Christopher G. Guglielmo, Jean‐Michel Weber

Bibliographic record

VenueJournal of Experimental Biology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsShiveringEnergeticsLipid oxidationBiologyEcologyAnimal scienceZoologyChemistryBiochemistryPhysiology

Abstract

fetched live from OpenAlex

The metabolic consequences of cold exposure and exercise are not well characterized in birds. Ruff sandpipers Philomachus pugnax are migrant shorebirds traveling between Africa and Siberia for up to 30,000 km annually. Our goal was to quantify the fuel selection pattern of these remarkable athletes during shivering and terrestrial locomotion. We used indirect calorimetry and nitrogen excretion analysis to measure their rates of lipid, carbohydrate and protein oxidation at different temperatures (22, 15, 10 or 5 degrees C) and different treadmill speeds (15, 20, 25, 30, 35 or 40 m min(-1)). Results show that lipid oxidation supplies nearly all the energy necessary to support shivering and running, and that the pattern of oxidative fuel selection is independent of shivering or running intensity. During shivering, total ATP production is unequally shared between lipids (82%), carbohydrates (12%) and proteins (6%). During running, lipids remain the dominant substrate (66%), with carbohydrates (29%) and proteins (5%) playing more minor roles. The prevailing use of lipids during intense shivering and high-speed running is not consistent with the fuel selection pattern observed in exercising and cold-exposed mammals. The exact mechanisms allowing birds to use lipids at extremely high rates are still largely unexplored, and quantifying the relative importance of different fuels during long-distance flight remains a major challenge for future research.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.309

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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 designBench or experimental
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

Citations55
Published2005
Admission routes1
Has abstractyes

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