Epilepsy and activity—A population‐based study
Bibliographic record
Abstract
PURPOSE: To compare the activity profiles of a nationally representative sample of individuals with epilepsy compared to the general population. METHODS: The Canadian Community Health Survey is a cross-sectional survey that uses a stratified cluster sample design to obtain information on Canadians 12 years of age or older. Data on activity and energy expenditure, among those aged 12-39 years, were compared for those who reported having epilepsy and the remainder of the population. RESULTS: Of the 53,552 respondents, 341 reported having epilepsy. There was no difference in the monthly frequency of leisure physical activity of >15 min duration between those who did and did not have epilepsy. The daily energy expenditure related to leisure physical activity was also similar between the two groups. The choice of leisure activity was similar, but those with epilepsy were more likely to use walking as a leisure physical activity and were less likely to be involved in ice hockey, weight training, and home exercise. DISCUSSION: These results suggest that the negative attitudes toward restricting access to physical activity do not appear to be adversely affecting the leisure activity of Canadian youth and young adults with epilepsy.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".