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Record W2111885945 · doi:10.1037/0021-843x.113.4.603

Cognitive-Neuropsychological Function in Chronic Physical Aggression and Hyperactivity.

2004· article· en· W2111885945 on OpenAlexafffund
Jean R. Séguin, Daniel S. Nagin, Jean‐Marc Assaad, Richard E. Tremblay

Bibliographic record

VenueJournal of Abnormal Psychology · 2004
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMcGill UniversityUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsPsychologyAggressionCognitionNeuropsychologyDevelopmental psychologyExecutive functionsNeuropsychological testClinical psychologyWorking memoryPsychiatry

Abstract

fetched live from OpenAlex

Histories of violence and of hyperactivity are both characterized by poor cognitive-neuropsychological function. However, researchers do not know whether these histories combine in additive or interactive ways. The authors tested 303 male young adults from a community sample whose trajectories of teacher-rated physical aggression and motoric hyperactivity from kindergarten to age 15 were well defined. No significant interaction was found. In a 1st model, both histories of problem behavior were independently associated with cognitive-neuropsychological function in most domains. In a second model controlling for IQ, General Memory, and test motivation, none of the three Working Memory tests (relevant to executive function) remained associated with physical aggression or hyperactivity. These results support an additive model but no specificity to executive function [corrected].

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)0.003
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
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 head0.044
GPT teacher head0.386
Teacher spread0.342 · 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

Citations132
Published2004
Admission routes2
Has abstractyes

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