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Record W2143901351 · doi:10.1098/rsbl.2011.0975

Wild geese do not increase flight behaviour prior to migration

2011· article· en· W2143901351 on OpenAlexaff
Steven J. Portugal, Jonathan A. Green, Craig R. White, Magella Guillemette, P. J. Butler

Bibliographic record

VenueBiology Letters · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité du Québec à Rimouski
FundersBiotechnology and Biological Sciences Research Council
KeywordsBiologyBird migrationBird flightEcologyFlight featherNocturnalZoologyAnimal scienceMoulting

Abstract

fetched live from OpenAlex

Hypertrophy of the flight muscles is regularly observed in birds prior to long-distance migrations. We tested the hypothesis that a large migratory bird would increase flight behaviour prior to migration, in order to cause hypertrophy of the flight muscles, and upregulate key components of the aerobic metabolic pathways. Implantable data loggers were used to record year-round heart rate in six wild barnacle geese (Branta leucopsis), and the amount of time spent in flight each day was identified. Time in flight per day did not significantly increase prior to either the spring or the autumn migration, both between time periods prior to migration (5, 10 and 15 days), or when compared with a control period of low activity during winter. The lack of significant increase in flight prior to migration suggests that approximately 22 min per day is sufficient to maintain the flight muscles in condition for prolonged long-distance flight. This apparent lack of a requirement for increased flight activity prior to migration may be attributable to pre-migratory mass gains in the geese increasing workload during short flights, potentially prompting hypertrophy of the flight muscles.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.998

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)0.0030.003

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 head0.016
GPT teacher head0.228
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

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

Citations25
Published2011
Admission routes1
Has abstractyes

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