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Record W4413467498 · doi:10.1139/cjz-2024-0154

Not hibernation ecology, but size matters—arousal metabolism of European bats in caves

2025· article· en· W4413467498 on OpenAlexvenueno aff
Petr Mrhálek, Erik Bachorec, Kateřina Zukalová, Heliana Dundarova

Bibliographic record

VenueCanadian Journal of Zoology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
FundersÚstav biologie obratlovců, Akademie věd ČR
KeywordsBiologyHibernation (computing)EcologyCaveTorporEcophysiologyZoologyBotanyThermoregulationPhotosynthesis

Abstract

fetched live from OpenAlex

Small endotherms have high rates of heat loss and, at low temperatures, require large amounts of energy to maintain stable body temperatures via endogenous heat production. To maintain energy balance during winter, many temperate-zone bats rely on hibernation. Although bats spend most of their time during hibernation at low body temperatures, most of their energy budget is allocated to costly arousals. We compared temporal and metabolic parameters of rewarming among four hibernating European bat species to test the hypothesis that hibernation ecology and body size influences the energetics of rewarming. We predicted that smaller species would have greater relative energy expenditure during arousals because of their higher rates of heat loss. Consistent with our prediction, two of the three parameters we measured (i.e., maximum rate of mass-specific oxygen consumption (VO2) during arousal and area under the mass-specific VO2 curve) were higher in the smaller species, although there was no difference in the time of peak mass-specific VO2. The results suggest that the duration of rewarming does not differ between the four studied species, but relative to their body size, smaller bats use more energy during arousal than larger bats, highlighting the importance of body size for energy demands during hibernation.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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