Julie Bouchard, professeure et chercheuse en neuropsychologie clinique
Bibliographic record
Abstract
Depuis son arrivée à l’UQAC il y a 13 ans, les intérêts de recherche de la professeure et chercheuse Julie Bouchard sont, entre autres, les effets de la musique sur les fonctions cognitives chez les personnes atteintes de dyslexie et d’un trouble déficitaire de l’attention ainsi que les robots d’assistance sociale chez la personne âgée en déclin cognitif et ayant différentes pathologies cérébrales telles que les troubles neurocognitifs (Alzheimer) et les atteintes cognitives de l’ataxie récessive spastique de Charlevoix- Saguenay. Elle s’implique activement au sein du Laboratoire d’intelligence ambiante pour la reconnaissance d’activités (LIARA), qui développe l’intelligence artificielle pour les personnes ayant des problèmes de santé, dont les déficiences cognitives.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".