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Record W2984780982 · doi:10.1002/dev.21933

Development of ultrasonic calls in rat pups follows similar patterns regardless of isolation distress

2019· article· en· W2984780982 on OpenAlexafffund
Rachel Stark, Allonna Harker, Sophia Salamanca, Sergio M. Pellis, Fangfang Li, Robbin Gibb

Bibliographic record

VenueDevelopmental Psychobiology · 2019
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWeaningDistressAnxietyContext (archaeology)PsychologyIsolation (microbiology)Developmental psychologySocial isolationPhysiologyAffect (linguistics)AudiologyInternal medicineBiologyMedicineClinical psychologyCommunicationPsychiatryBioinformatics

Abstract

fetched live from OpenAlex

Ultrasonic vocalizations (USVs) emitted by rat pups have been extensively studied in the context of isolation from their mother and littermates. The heightened call rate of isolation-induced USVs indicates increased anxiety, whereas other acoustic parameters, such as frequency and call duration, are thought to be useful in reflecting developmental changes, which by weaning have developed into their adult form. However, it is possible that stress can affect the quality as well as the quantity of calls, and that as the pups become more mobile, the effects of the stress may change. Therefore, in the present study rats were tested in a test arena either in isolation or with littermates, so as to assess the effects of isolation stress on the developmental changes reported in the literature. Rat pups of both sexes were tested on multiple days from postnatal day (PND) 7 to weaning. Overall, the main changes in the frequency, duration, and types of calls were accounted for by age. The effects of isolation were minor, as were sex differences. This study indicates that the development of USVs in infant rats is a robust process and seemingly resistant to the effects of isolation-induced stress.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.999

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)0.0020.000

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 head0.025
GPT teacher head0.312
Teacher spread0.287 · 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 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

Citations23
Published2019
Admission routes2
Has abstractyes

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