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Record W2714544529 · doi:10.7202/1040036ar

DÉVELOPPEMENT COGNITIF DES ENFANTS ÉPILEPTIQUES : CONTRIBUTION DU STRESS

2017· article· fr· W2714544529 on OpenAlexaffvenue
Fanny Thébault‐Dagher, Lionel Carmant, Jocelyn Gravel, Sonia Lupien, Catherine M. Herba, Sarah Lippé

Bibliographic record

VenueRevue québécoise de psychologie · 2017
Typearticle
Languagefr
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsPhilosophyHumanities

Abstract

fetched live from OpenAlex

L’épilepsie est un désordre neurologique souvent infantile associé à des comorbidités qui impliquent des troubles cognitifs. Depuis quelques années, les études des chercheurs suggèrent que la qualité de vie des personnes atteintes d’épilepsie est plus sévèrement impactée par les comorbidités associées à la maladie que par les crises. Il importe donc de diminuer la sévérité des troubles cognitifs chez les personnes épileptiques. Dans cet article, nous relevons les hypothèses de la littérature actuelle qui stipulent que le stress pourrait être un facteur affectant négativement le développement cognitif des enfants épileptiques. Ainsi, nous décrivons les atteintes neuropsychologiques inhérentes aux syndromes convulsifs, la relation biologique du stress et la relation entre le stress et les syndromes convulsifs. Deux modes d’action, évoqués par les chercheurs, par lesquels le stress serait un facteur aggravant les comorbidités des personnes qui présentent un syndrome convulsif seront aussi décrits.

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 score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.068
GPT teacher head0.393
Teacher spread0.326 · 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
Published2017
Admission routes2
Has abstractyes

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