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Record W2139027496 · doi:10.1890/080187

Could localized warm areas inside cold caves reduce mortality of hibernating bats affected by white‐nose syndrome?

2009· review· en· W2139027496 on OpenAlex
Justin G. Boyles, Craig K. R. Willis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2009
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsHibernation (computing)BiologyPopulationEcologyZoologyTorporWhite (mutation)ThermoregulationDemography

Abstract

fetched live from OpenAlex

White‐nose syndrome (WNS) is a mysterious condition affecting populations of hibernating bats in the northeastern US. Little is known about its physiological effects on bats and no intervention has so far been proposed to slow associated mortality. We use an individual‐based population model to examine how disruption of normal hibernation or pre‐hibernation physiology could lead to the pattern of mortality that has been observed. We present evidence that artificial warming of localized areas within hibernacula could increase survival of WNS‐affected bats during winter by lessening the energetic costs of periodic arousals. The model suggests that localized thermal refugia of 28°C could improve survival by up to 75%, depending on how WNS acts to disrupt energy balance. This approach has yet to be tested, but it could serve as a stopgap measure to slow population declines until a solution is found, or to preserve remnant bat populations if WNS becomes ubiquitous throughout the ranges of affected species.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.807
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.235
Teacher spread0.218 · 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