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Record W2102368955 · doi:10.3922/j.psns.2011.3.010

Relationships between executive functions tasks in late childhood.

2011· article· en· W2102368955 on OpenAlexaboutno aff
Janice R. Pureza, Geise Machado Jacobsen, Rodrigo Grassi de Oliveira, Róchele Paz Fonseca

Bibliographic record

VenuePsychology & Neuroscience · 2011
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsnot available
Fundersnot available
KeywordsExecutive functionsPsychologyDevelopmental psychologyCognitive psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

Executive functions (EF) is a general term that refers to cognitive processes designed to organize and adapt human behavior in situations that require planning and decision making, problem solving, initiation and inhibition of actions, and adapting to changes. Among the main components of executive processes, we can emphasize the ability to inhibit and to present cognitive flexibility due to changes. Understanding the relationships among the various components of EF in adults and children has been a focus in the literature. However, these processes are complex and multiple. The present study sought to determine whether correlations exist among performances measured by different tools used to evaluate EF in school-age children. The sample comprised 59 children aged 8 to 12 years attending public schools. Participants were assessed using verbal fluency tasks and narrative discourse with the Montreal Battery of Evaluation of Communication-MAC Battery, random-number generation, the Hayling Test, the Bells Test, and the n-back test. Correlation analyses were performed using Pearson's correlation coefficient. The results suggested a closer relationship among some components of the evaluation of EF, especially among tasks that assess inhibition and cognitive flexibility.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.214
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.353
Teacher spread0.196 · 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 teacher head, 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

Citations16
Published2011
Admission routes1
Has abstractyes

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