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Record W4416252868 · doi:10.1111/eth.70033

Greeting Vocalizations in Domestic Cats Are More Frequent With Male Caregivers

2025· article· en· W4416252868 on OpenAlexaff
Yasemin Salgırlı Demirbaş, Kaan Kerman, Durmuş Atılgan, Melis Ünler

Bibliographic record

VenueEthology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Prince Edward Island
FundersTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsContext (archaeology)CATSSocial environmentSocial relationBehavioral analysisVocal communicationFeeding behavior

Abstract

fetched live from OpenAlex

ABSTRACT Greeting is an essential component of social relationships, facilitating harmonious communication and reinforcing social bonds. The domestic cat ( Felis catus ) provides a valuable model system for investigating greeting behavior, particularly in the context of interspecific interactions with humans. In this study, we examined how cats ( n = 31) greet their human caregivers in their natural home environments. Using 22 behavioral measures, we explored how these behaviors related to one another during 100‐s greeting sessions. We also tested whether demographic factors such as the influenced the amount of greeting behavior expressed by household cats. Our results showed that cats vocalized more frequently toward male caregivers, while no other demographic factor had a discernible effect on the frequency or duration of greetings. Correlational analyses revealed two interrelated behavioral patterns: affiliative and displacement‐like behaviors. These findings suggest that cat greetings are multimodal, may reflect different motivational or emotional states, and can be modulated by external factors such as caregiver sex.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.352

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 head0.014
GPT teacher head0.362
Teacher spread0.348 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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