Epilepsy and motor vehicle driving - A Symposium held in Québec City, November 1998
Bibliographic record
Abstract
BACKGROUND: This report summarizes an invitational symposium on epilepsy and Canadian laws governing motor vehicle driving held in Québec City in November 1998. METHODS: Invited neurological experts from Canada, the USA, and Europe; and representatives of provincial and territorial licensing bodies, the Canadian Council of Motor Transport Administrators, the Canadian Medical Protective Association, and the Canadian Medical Association participated. An edited version of transcribed audiotapes was prepared. Specific issues discussed were whether or not a physician should be required to report a patient with epilepsy to the licensing authority (mandatory reporting), the nature and quantification of the risks posed by epileptic drivers, and what would be a reasonable law regulating driving by people with epilepsy in Canada. RESULTS: The consensus among medical experts was that mandatory reporting should be abolished in Canada and that a 6-12 month seizure-free period was appropriate before most patients could return to driving private cars. Experts also believed that these standards should be uniform across Canada. There was strong disagreement with the recommendation of the Canadian Medical Association that all such drivers be reported to provincial licensing authorities even in provinces without mandatory reporting rules. CONCLUSIONS: Physicians should be familiar with and follow the rules regarding epilepsy and driving in the provinces where they practice. Nevertheless, current evidence is against mandatory physician reporting of drivers with epilepsy and the neurologists recommended that this be abolished throughout Canada. Shorter seizure-free intervals should also be considered before resuming driving of private cars.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
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".