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Record W2731946439 · doi:10.1093/icb/icx068

Do Bar-Headed Geese Train for High Altitude Flights?

2017· article· en· W2731946439 on OpenAlexafffund
Lucy A. Hawkes, Nyambayar Batbayar, P. J. Butler, Beverley Chua, Peter B. Frappell, Jessica U. Meir, William K. Milsom, Tseveenmyadag Natsagdorj, Nicole Parr, Graham R. Scott, John Y. Takekawa, Martin WikeIski, Matthew J. Witt, Charles M. Bishop

Bibliographic record

VenueIntegrative and Comparative Biology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsMcMaster UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaBiotechnology and Biological Sciences Research CouncilDirectorate for Biological Sciences
KeywordsAltitude (triangle)Effects of high altitude on humansHeart rateHypoxia (environmental)Low altitudeAnimal scienceContext (archaeology)BiologyBlood pressureOxygenAnatomyEndocrinologyChemistryMathematics

Abstract

fetched live from OpenAlex

SYNOPSIS: Exercise at high altitude is extremely challenging, largely due to hypobaric hypoxia (low oxygen levels brought about by low air pressure). In humans, the maximal rate of oxygen consumption decreases with increasing altitude, supporting progressively poorer performance. Bar-headed geese (Anser indicus) are renowned high altitude migrants and, although they appear to minimize altitude during migration where possible, they must fly over the Tibetan Plateau (mean altitude 4800 m) for much of their annual migration. This requires considerable cardiovascular effort, but no study has assessed the extent to which bar-headed geese may train prior to migration for long distances, or for high altitudes. Using implanted loggers that recorded heart rate, acceleration, pressure, and temperature, we found no evidence of training for migration in bar-headed geese. Geese showed no significant change in summed activity per day or maximal activity per day. There was also no significant change in maximum heart rate per day or minimum resting heart rate, which may be evidence of an increase in cardiac stroke volume if all other variables were to remain the same. We discuss the strategies used by bar-headed geese in the context of training undertaken by human mountaineers when preparing for high altitude, noting the differences between their respective cardiovascular physiology.

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 score0.364
Threshold uncertainty score0.796

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 studies0.0010.001
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 head0.061
GPT teacher head0.355
Teacher spread0.294 · 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

Citations12
Published2017
Admission routes2
Has abstractyes

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