Evidence map›Paper›PMID 41034519›Full record

ArticleBehavior research methods2025

A year of nouns from English-learning infants' daily lives: The SEEDLingS-Nouns dataset.

Evgenii Kalenkovich, Sharath Koorathota, Shaelise Tor, Andrei Amatuni, Shannon Egan-Dailey, Charlotte Moore, Catherine Laing, Hallie Garrison, Gladys Baudet, Federica Bulgarelli and 3 more

Abstract readDataset
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In one paragraph

Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Evgenii KalenkovichHarvard University, 33 Kirkland Street, Cambridge, MA, 02138, USA.
Sharath KoorathotaUniversity of Rochester, Rochester, NY, USA.
Shaelise TorUniversity of Rochester, Rochester, NY, USA.
Andrei AmatuniUniversity of Texas-Austin, Austin, TX, USA.
Shannon Egan-DaileyDuke University, Durham, NC, USA.
Charlotte MooreConcordia University, Montreal, Canada.
Catherine LaingUniversity of York, York, UK.
Hallie GarrisonDuke University, Durham, NC, USA.
Gladys BaudetDuke University, Durham, NC, USA.
Federica BulgarelliUniversity at Buffalo, Buffalo, NY, USA.
Sarp UnerDuke University, Durham, NC, USA.
Lillianna RighterHarvard University, 33 Kirkland Street, Cambridge, MA, 02138, USA.
Elika BergelsonHarvard University, 33 Kirkland Street, Cambridge, MA, 02138, USA. elika_bergelson@fas.harvard.edu.

Funding

Within- and between- talker variability and word learningF32HD101216 · NICHD · DUKE UNIVERSITY · PI BULGARELLI, FEDERICA · 2019 to 2022
$190k
NICHD NIH HHS F32 HD101216NIH HHS 5DP5OD019812-05
6 · The paper itself

Abstract

This paper describes a dataset consisting of manually annotated nouns from a corpus of longitudinal day-long audio and hour-long video recordings collected monthly from 44 babies from age 6 months to age 17 months. This dataset was created as part of a larger project, called SEEDLingS, that examines the development of infants' language comprehension before and after their first birthday, from earliest comprehension to the early days of word production. This paper provides an overview of the corpus, describes how and why the nouns from the corpus were annotated, and discusses considerations for the reuse of this dataset for future work. The described annotations and relevant metadata are publicly available alongside this manuscript.

Indexed as

ComprehensionLanguageLanguage DevelopmentFemaleHumansInfantMaleCorpusHome recordingsInfancyLanguage acquisition

Identifiers

PMID41034519

What OpenQuestion holds

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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.