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Record W2972917857 · doi:10.1002/dev.21919

Frontal brain maturation and the stability of children’s shyness

2019· article· en· W2972917857 on OpenAlexafffund
Louis A. Schmidt, Kristie L. Poole

Bibliographic record

VenueDevelopmental Psychobiology · 2019
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsShynessPsychologyAnxietyDevelopmental psychologySocial anxietyPsychiatry

Abstract

fetched live from OpenAlex

Recent evidence suggests that relative to nonshy children, shy children exhibit a lower overall frontal EEG alpha/delta ratio (ADR) during middle childhood, possibly reflecting relatively less frontal brain maturation at this age. We examined this same ADR measure in relation to the stability of observed shyness and parent-reported child social anxiety measured across two laboratory visits separated by approximately 1 year during late childhood in 51 children (33% female, age range 10-16 years). We found that the overall frontal ADR score was significantly lower among children with high, stable observed shyness and parent-reported child social anxiety compared to children in the low, stable class. Findings provide convergent evidence suggesting that the stability of shyness in late childhood may be linked to relatively less overall frontal brain maturation at this age. We speculate on the adaptive function of delaying frontal brain maturation in the origins and maintenance of children's shyness.

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)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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

Citations18
Published2019
Admission routes2
Has abstractyes

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