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Record W2025839334 · doi:10.1644/09-mamm-s-084r.1

What Can Birds Tell Us about the Migration Physiology of Bats?

2009· article· en· W2025839334 on OpenAlex
Liam P. McGuire, Christopher G. Guglielmo

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

VenueJournal of Mammalogy · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsTorporBiologyBird migrationEcologyForagingZoologyThermoregulation

Abstract

fetched live from OpenAlex

Many species of bats undergo annual migrations, in some cases covering distances of 1,000 km or more. However, very little is known about the physiological and biochemical mechanisms underlying bat migration. In contrast, the physiology of migrating birds has been studied for decades and many migration-related changes have been documented. Although bats and birds evolved flight and long-distance migration independently, they have likely experienced many similar selective pressures. We therefore suggest that knowledge of bird migration physiology can be used to generate predictions for emerging studies of bat migration physiology. In this review, we discuss major physiological and biochemical adaptations relating to fuel acquisition and fuel utilization. For each, we summarize knowledge gained from migration studies of birds and bats (if any) and make predictions of bat migration physiology. For many aspects, we predict that bats will have evolved similar physiological mechanisms to birds. However, there are some potentially major differences in the energetic models for bats and birds, including torpor, fuel selection at high-intensity exercise, and trade-offs between reproduction and migration.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.150

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 head0.017
GPT teacher head0.227
Teacher spread0.210 · 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