MétaCan
Menu
Back to cohort
Record W2594427310 · doi:10.1111/cdev.12777

Naturalistic Language Recordings Reveal “Hypervocal” Infants at High Familial Risk for Autism

2017· article· en· W2594427310 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChild Development · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Alberta
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Biomedical Imaging and BioengineeringNational Institute of Child Health and Human DevelopmentNational Institute of Environmental Health SciencesNational Institute of Mental HealthSimons FoundationNational Institutes of HealthNational Science Foundation
KeywordsPsychologyAutismDevelopmental psychologyLanguage developmentNaturalismCognitive psychology

Abstract

fetched live from OpenAlex

Children's early language environments are related to later development. Little is known about this association in siblings of children with autism spectrum disorder (ASD), who often experience language delays or have ASD. Fifty-nine 9-month-old infants at high or low familial risk for ASD contributed full-day in-home language recordings. High-risk infants produced more vocalizations than low-risk peers; conversational turns and adult words did not differ by group. Vocalization differences were driven by a subgroup of "hypervocal" infants. Despite more vocalizations overall, these infants engaged in less social babbling during a standardized clinic assessment, and they experienced fewer conversational turns relative to their rate of vocalizations. Two ways in which these individual and environmental differences may relate to subsequent development are discussed.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.025
GPT teacher head0.301
Teacher spread0.276 · 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