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Record W2012667336 · doi:10.1037/0012-1649.44.1.205

Developmental differences in error-related ERPs in middle- to late-adolescent males.

2008· article· en· W2012667336 on OpenAlexafffund
Diane L. Santesso, Sidney J. Segalowitz

Bibliographic record

VenueDevelopmental Psychology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyAnterior cingulate cortexError-related negativityNeurochemicalNegativity effectDevelopmental psychologyTask (project management)AudiologyEvent-related potentialElectroencephalographyCognitive psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

Although there are some studies documenting structural brain changes during late adolescence, there are few showing functional brain changes over this period in humans. Of special interest would be functional changes in the medial frontal cortex that reflect response monitoring. In order to examine such age-related differences, the authors analyzed event-related potentials following errors in a visual flanker task and a go/no-go task in adolescent males, 15-16 and 18-20 years old. Response times and accuracy were comparable between groups on each task, but the younger group made more go/no-go errors, suggesting this task was more difficult. Error-related negativity, thought to be generated in the anterior cingulate cortex (ACC), had greater amplitude for the older adolescents on both tasks; thus the increased errors are not simply due to performance level differences. Results from this study suggest that the ACC, which supports response monitoring, is late to mature due to age-related structural or neurochemical changes.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.300
GPT teacher head0.371
Teacher spread0.071 · 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

Citations84
Published2008
Admission routes2
Has abstractyes

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