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Record W1658173887

Estudos de neuroimagem sobre funções executivas: evidências da técnica fNIRS

2008· article· pt· W1658173887 on OpenAlexaff
Yves Joanette, Ana Inés Ansaldo, Maria alice De Mattos Pimienta Parente, Róchele Paz Fonseca, Christian Haag Kristensen, Lílian Cristine Scherer

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2008
Typearticle
Languagept
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsychologyStroop effectCognitionFunctional near-infrared spectroscopyNeuroimagingExecutive functionsCognitive psychologyFunctional neuroimagingVerbal fluency testNeuropsychologyNeurosciencePrefrontal cortex
DOInot available

Abstract

fetched live from OpenAlex

Functional Near-Infrared Spectroscopy (fNIRS) has emerged as a valuable tool to investigate human cognition. One of the most relevant cognitive aspects to be further explored is the role of executive functions (EF) in cognitive tasks’ performance. The aim of this article is to review empirical studies on EF processing conducted by means of fNIRS. This systematic review has shown, among other findings, that the majority of the studies has focused (a) on the neural correlates of cognitive processing, (b) on the EF components of verbal fluency and Stroop tasks, (c) mainly on healthy young adults populations, and (d) on clinical samples, represented most frequently by schizophrenic patients. The reviewed technique can be considered valid for examining neurobiological correlates of executive functions. \n\nKeywords: Executive functions; neuroimaging; fNIRS; systematic review.

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)0.018
metaresearch head score (Gemma)0.065
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.008
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
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 head0.031
GPT teacher head0.273
Teacher spread0.242 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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