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Record W3083608533 · doi:10.46278/j.ncacn.20170726

Les survivants d’une tumeur cérébrale et d’un traumatisme cranio-cérébral sont-ils si différents? Une revue systématisée de la littérature

2017· article· fr· W3083608533 on OpenAlexaffvenue
Justine Arneberg-Joncas, Marie‐Claude Blais

Bibliographic record

VenueNeuropsychologie clinique et appliquée · 2017
Typearticle
Languagefr
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsMedicineGynecologyHumanitiesArt

Abstract

fetched live from OpenAlex

Le traumatisme craniocérébral (TCC) et les tumeurs cérébrales (TC) sont deux atteintes cérébrales acquises (ACA) pouvant entrainer d’importantes répercussions à long terme. Peu d’études ont décrit le vécu à l’âge adulte des personnes ayant subi un TCC ou une TC pédiatrique et, à ce jour, aucune d’elles n’a comparé ces deux populations. Cette revue de la littérature décrit et compare les répercussions sur les plans cognitif, psychosocial et socioprofessionnel de ces deux types d’ACA. Une recension des écrits a permis de sélectionner 13 et 17 études réalisées auprès d’adultes (18-35 ans) ayant subi, respectivement, un TCC et une TC pendant l’enfance. Ces deux populations cliniques présentent un risque élevé de vivre encore à l’âge adulte des difficultés cognitives et psychosociales susceptibles de nuire au fonctionnement quotidien et socioprofessionnel. Une connaissance plus approfondie des caractéristiques similaires et distinctes aux deux populations pourrait permettre d’améliorer les interventions et les ressources qui leur sont offertes.

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)0.013
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.011
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0010.001

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 head0.108
GPT teacher head0.436
Teacher spread0.328 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2017
Admission routes2
Has abstractyes

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