Evidence map›Paper›PMID 33094407›Full record

ArticleAnimal cognition2021

A machine learning approach to infant distress calls and maternal behaviour of wild chimpanzees.

Guillaume Dezecache, Klaus Zuberbühler, Marina Davila-Ross, Christoph D Dahl

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Animal cognition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. The growing methodological toolkit for identifying and studying social learning and culture in non-human animals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Review
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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

4 authors at 4 institutions in 5 countries.

Guillaume DezecacheInstitute of Biology, University of Neuchâtel, Neuchâtel, Switzerland. guillaume.dezecache@gmail.com.ORCID http://orcid.org/0000-0002-9366-6287
Klaus ZuberbühlerInstitute of Biology, University of Neuchâtel, Neuchâtel, Switzerland.
Marina Davila-RossDepartment of Psychology, University of Portsmouth, Portsmouth, England, UK.
Christoph D DahlInstitute of Biology, University of Neuchâtel, Neuchâtel, Switzerland. christoph.d.dahl@gmail.com.
International Gorilla Conservation Programme · RWTaipei Medical University-Shuang Ho Hospital · TWUniversity of Portsmouth · GBUniversity of St Andrews · GB

Funding

FP7 Ideas: European Research Council 283871Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung PZ00P3_154741
6 · The paper itself

Abstract

Distress calls are an acoustically variable group of vocalizations ubiquitous in mammals and other animals. Their presumed function is to recruit help, but there has been much debate on whether the nature of the disturbance can be inferred from the acoustics of distress calls. We used machine learning to analyse episodes of distress calls of wild infant chimpanzees. We extracted exemplars from those distress call episodes and examined them in relation to the external event triggering them and the distance to the mother. In further steps, we tested whether the acoustic variants were associated with particular maternal responses. Our results suggest that, although infant chimpanzee distress calls are highly graded, they can convey information about discrete problems experienced by the infant and about distance to the mother, which in turn may help guide maternal parenting decisions. The extent to which mothers rely on acoustic cues alone (versus integrate other contextual-visual information) to decide upon intervening should be the focus of future research.

Indexed as

Maternal BehaviorPan troglodytesAcousticsAnimalsFemaleHumansMachine LearningMothersCryingMachine learningPan troglodytesSupport vector machineWhimpers

Identifiers

PMID33094407
OpenAlexW3093572898

What OpenQuestion holds

Textmetadata
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.