Neurological Diseases, Disorders and Injuries in Canada: Highlights of a National Study
Bibliographic record
Abstract
The National Population Health Study of Neurological Conditions, a partnership between Neurological Health Charities Canada and the Government of Canada, was the largest study of neurological diseases, disorders, and injuries ever conducted in Canada. Undertaken between 2009 and 2013, the expansive program of research addressed the epidemiology, impacts, health services, and risk factors of 18 neurological conditions and estimated the health outcomes and costs of these conditions in Canada through 2031. This review summarizes highlights from the component projects of the study as presented in the synthesis report, Mapping Connections: An Understanding of Neurological Conditions in Canada. The key findings included new prevalence and incidence estimates, documentation of the diverse and often debilitating effects of neurological conditions, and identification of the utilization, economic costs, and current limitations of related health services. The study findings will support health charities, governments, and other stakeholders to reduce the impact of neurological conditions in Canada.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".