Evidence map›Paper›PMID 39507993›Full record

ArticleRoyal Society open science2024

Beyond bigrams: call sequencing in the common marmoset (

Alexandra B Bosshard, Judith M Burkart, Paola Merlo, Chundra Cathcart, Simon W Townsend, Balthasar Bickel

Abstract read
In one paragraph

Article in Royal Society open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Utterance evolution: the road to generative, combinatorial communicators.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  2. Article
  3. Review
  4. Primate ACC encodes natural vocal interactions in a 'cocktail party'.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexandra B BosshardDepartment of Comparative Language Science, University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0003-4604-5952
Judith M BurkartCenter for the Interdisciplinary Study of Language Evolution (ISLE), University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0002-6229-525X
Paola MerloDepartment of Linguistics, University of Geneva, Geneva, Switzerland.
Chundra CathcartDepartment of Comparative Language Science, University of Zurich, Zurich, Switzerland.
Simon W TownsendDepartment of Comparative Language Science, University of Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0003-1504-1801
Balthasar BickelDepartment of Comparative Language Science, University of Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last two decades, an emerging body of research has demonstrated that non-human animals exhibit the ability to combine context-specific calls into larger sequences. These structures have frequently been compared with language's syntax, whereby linguistic units are combined to form larger structures, and leveraged to argue that syntax might not be unique to language. Currently, however, the overwhelming majority of examples of call combinations are limited to simple sequences comprising just two calls which differ dramatically from the open-ended hierarchical structuring of the syntax found in language. We revisit this issue by taking a whole-repertoire approach to investigate combinatoriality in common marmosets (

Indexed as

animal communicationcall sequencescommon marmosetsMarkov chain modelswhole-repertoire analysis

Identifiers

PMID39507993
PMCPMC11537759

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.