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Record W2089845768 · doi:10.1371/journal.pone.0073045

Ultrasonic Vocalizations Emitted by Flying Squirrels

2013· article· en· W2089845768 on OpenAlexafffundabout
Meghan N. Murrant, Jeff Bowman, Colin J. Garroway, Brian Prinzen, Heather W. Mayberry, Paul A. Faure

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsMcMaster UniversityMinistry of Natural Resources and ForestryTrent University
FundersNatural Sciences and Engineering Research Council of CanadaTrent UniversityMinistry of Natural Resources
KeywordsUltrasonic sensorBioacousticsAcousticsSquirrel monkeyBiologyEcologyPhysics

Abstract

fetched live from OpenAlex

Anecdotal reports of ultrasound use by flying squirrels have existed for decades, yet there has been little detailed analysis of their vocalizations. Here we demonstrate that two species of flying squirrel emit ultrasonic vocalizations. We recorded vocalizations from northern (Glaucomys sabrinus) and southern (G. volans) flying squirrels calling in both the laboratory and at a field site in central Ontario, Canada. We demonstrate that flying squirrels produce ultrasonic emissions through recorded bursts of broadband noise and time-frequency structured frequency modulated (FM) vocalizations, some of which were purely ultrasonic. Squirrels emitted three types of ultrasonic calls in laboratory recordings and one type in the field. The variety of signals that were recorded suggest that flying squirrels may use ultrasonic vocalizations to transfer information. Thus, vocalizations may be an important, although still poorly understood, aspect of flying squirrel social biology.

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 score0.201
Threshold uncertainty score0.995

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)0.0130.005

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 head0.029
GPT teacher head0.213
Teacher spread0.184 · 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

Citations24
Published2013
Admission routes3
Has abstractyes

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