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Evidence for a Gene-Environment Interaction in Predicting Behavioral Inhibition in Middle Childhood

2005· article· en· W2113098321 on OpenAlexaff
Nathan A. Fox, Kate E. Nichols, Heather A. Henderson, Kenneth H. Rubin, Louis A. Schmidt, Dean H. Hamer, Monique Ernst, Daniel S. Pine

Bibliographic record

VenuePsychological Science · 2005
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcMaster University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsPsychologySerotonin transporterDevelopmental psychologyBehavioral inhibitionAlleleSocial relationGene–environment interactionPolymorphism (computer science)Social environmentGeneGeneticsSocial psychologyGenotypePsychiatryAnxietyBiology

Abstract

fetched live from OpenAlex

Gene-environment interactions are presumed to shape human behavior during early development. However, no human research has demonstrated that such interactions lead to stable individual differences in fear responses. We tested this possibility by focusing on a polymorphism in the promoter region of the gene for the serotonin transporter (5-HTT). This polymorphism has been linked to many indices of serotonin activity. Specifically, we tested the hypothesis that an interaction between children's 5-HTT status and maternal reports of social support predicts inhibited behavior with unfamiliar peers in middle childhood. Results were consistent with this hypothesis: Children with the combination of the short 5-HTT allele and low social support had increased risk for behavioral inhibition in middle childhood.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.211
GPT teacher head0.449
Teacher spread0.238 · 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

Citations265
Published2005
Admission routes1
Has abstractyes

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