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Record W2846750155 · doi:10.1093/cz/zoy055

Ontogeny of vocal rhythms in harbor seal pups: an exploratory study

2018· article· en· W2846750155 on OpenAlexaff
Andrea Ravignani, Christopher T. Kello, Koen de Reus, Sonja A. Kotz, Simone Dalla Bella, Margarita Méndez-Aróstegui, Beatriz Rapado-Tamarit, Ana Rubio‐García, Bart de Boer

Bibliographic record

VenueCurrent Zoology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversité de MontréalInternational Laboratory for Brain, Music and Sound Research
FundersFonds Wetenschappelijk Onderzoek
KeywordsRhythmOntogenySeal (emblem)BiologyZoologyExploratory researchCommunicationPsychologyGeographyMedicineInternal medicineAnthropologyArchaeologyGeneticsSociology

Abstract

fetched live from OpenAlex

. An important feature of vocalizations is their temporal and rhythmic structure, and understanding vocal timing and rhythms in harbor seals is critical to a cross-species hypothesis in evolutionary neuroscience that links vocal learning, rhythm perception, and synchronization. This study utilized analytical techniques that may best capture rhythmic structure in pup vocalizations with the goal of examining whether (1) harbor seal pups show rhythmic structure in their calls and (2) rhythms evolve over time. Calls of 3 wild-born seal pups were recorded daily over the course of 1-3 weeks; 3 temporal features were analyzed using 3 complementary techniques. We identified temporal and rhythmic structure in pup calls across different time windows. The calls of harbor seal pups exhibit some degree of temporal and rhythmic organization, which evolves over puppyhood and resembles that of other species' interactive communication. We suggest next steps for investigating call structure in harbor seal pups and propose comparative hypotheses to test in other pinniped species.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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

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 head0.052
GPT teacher head0.314
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2018
Admission routes1
Has abstractyes

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