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Record W2093637653 · doi:10.1196/annals.1308.039

Development of Error‐Monitoring Event‐Related Potentials in Adolescents

2004· article· en· W2093637653 on OpenAlexaff
Patricia L. Davies, Sidney J. Segalowitz, William J. Gavin

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2004
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsBrock University
FundersNational Institute of Mental Health
KeywordsError-related negativityNegativity effectEvent-related potentialPsychologyAnterior cingulate cortexAudiologyDevelopmental psychologyLatency (audio)Affect (linguistics)ElectroencephalographyCognitionNeuroscienceMedicineCommunication

Abstract

fetched live from OpenAlex

In order to study the maturation of neurobehavioral systems involved in affect regulation and behavioral choices during adolescence, we examined brain activity associated with response monitoring and error detection using event-related potentials (ERPs). In a visual flanker test, trials with incorrect responses elicit ERP components including an error-related negativity (ERN) and a later error-positivity (Pe). We examined the amplitude and latency of the ERN and Pe of incorrect responses in 124 children from 7 to 18 years of age. The ERN amplitude in error trials increased with age although this was qualified by a nonlinear change. The quadratic distribution of the ERN indicated an initial drop in amplitude (lowest at age 10 for girls; age 13 for boys) with a subsequent rise through adolescence. The Pe amplitude did not change with age. Results are discussed with respect to continued maturation of the anterior cingulate cortex and possible influences on adolescent behaviors.

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 score0.001
Threshold uncertainty score0.003

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 head0.352
GPT teacher head0.444
Teacher spread0.092 · 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

Citations81
Published2004
Admission routes1
Has abstractyes

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