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Record W2755239050 · doi:10.7554/elife.26686

Cyclic bouts of extreme bradycardia counteract the high metabolism of frugivorous bats

2017· article· en· W2755239050 on OpenAlexafffund
M. Teague O’Mara, Martin Wikelski, Christian C. Voigt, Andries Ter Maat, Henry S. Pollock, Gary Burness, Lanna M. Desantis, Dina K. N. Dechmann

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsTrent University
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsNatural Sciences and Engineering Research Council of CanadaMax-Planck-Instituts für OrnithologieUniversität KonstanzNational Geographic Society
KeywordsFrugivoreBradycardiaEcologyEnergy expenditureEnergy exchangeBiologyEnergy metabolismMetabolic rateEnergeticsStarvationHeart rateEndocrinologyAtmospheric sciencesPhysics

Abstract

fetched live from OpenAlex

Active flight requires the ability to efficiently fuel bursts of costly locomotion while maximizing energy conservation during non-flying times. We took a multi-faceted approach to estimate how fruit-eating bats (Uroderma bilobatum) manage a high-energy lifestyle fueled primarily by fig juice. Miniaturized heart rate telemetry shows that they use a novel, cyclic, bradycardic state that reduces daily energetic expenditure by 10% and counteracts heart rates as high as 900 bpm during flight. Uroderma bilobatum support flight with some of the fastest metabolic incorporation rates and dynamic circulating cortisol in vertebrates. These bats will exchange fat reserves within 24 hr, meaning that they must survive on the food of the day and are at daily risk of starvation. Energetic flexibly in U. bilobatum highlights the fundamental role of ecological pressures on integrative energetic networks and the still poorly understood energetic strategies of animals in the tropics.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.352

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 head0.034
GPT teacher head0.236
Teacher spread0.202 · 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

Citations67
Published2017
Admission routes2
Has abstractyes

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