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Record W6929819457 · doi:10.5061/dryad.qjq2bvqp4

Reproductive state alters vocal characteristics of female North American red squirrels (Tamiasciurus hudsonicus)

2023· dataset· en· W6929819457 on OpenAlexaff

Bibliographic record

VenueDRYAD · 2023
Typedataset
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMatingEstrous cycleVocal communicationAnimal communicationReproductive successReceptivityReproductionCourtshipMating system

Abstract

fetched live from OpenAlex

Female advertisement of reproductive state and receptivity has the potential to play a large role in the mating systems of many taxa, but investigations of this phenomenon are underrepresented in the literature. North American red squirrels (Tamiasciurus hudsonicus) are highly territorial and engage in scramble competition mating, with males converging from spatially disparate territories to engage in mating chases. Given the narrow estrus window exhibited in this species, the ubiquitous use of vocalizations to advertise territory ownership, and the high synchronicity of males arriving from distant territories, we hypothesized that female vocalizations contain cues relating to their estrous state. To test this hypothesis, we examined the spectral and temporal properties of female territorial rattle vocalizations collected from females of known reproductive condition over 3 years. While we found no distinct changes associated with estrus specifically, we did identify significant changes in the spectral characteristics of rattles relating to both female body mass and reproductive state relative to parturition. To the best of our knowledge, this is the first evidence of changes in vocal characteristics associated with late pregnancy in a non-human mammal.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.036
GPT teacher head0.305
Teacher spread0.269 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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