Stroke in Railway Workers, Pilots and Commercial Vehicle Operators: The Risk of a Future Event
Bibliographic record
Abstract
Medical guidelines, for individuals who have had a cerebrovascular event and who work in occupations where critical attention is required, lack consistency between occupations and across different areas of the world. Airline pilots, railway engineers and commercial vehicle operators are examples of individuals who cross international boarders frequently and need guidelines for safe return to work after an initial stroke. These individuals are at risk of a second catastrophic event including death, a myocardial infarction, syncope, seizures, or recurrent ischemic or hemorrhagic stroke. Medical guidelines should include occupational risk level, diagnosis of the initial event, assessment of the patient by medical evaluation and testing, risk factor evaluation and suggestions for further testing. A risk threshold to determine if an individual will go on to have a second event, stratified by diagnosis and other risk factors, should be stated in these guidelines. However, the risk that an individual in the working age group will go on to have a second event is not well understood. The first paper of this thesis is a narrative overview of the current medical guidelines in place for air, rail and road transport in Canada, the USA, the UK and Australia. The second paper is a systematic review and meta analysis looking at the risk that an individual with a first ever cerebrovascular event in the working age group will go on to have a catastrophic event.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".