Medical Cases Adjudicated by the Transportation Appeal Tribunal of Canada: 2000–2018
Bibliographic record
Abstract
INTRODUCTION: In Canada, aviators and seafarers are required to be medically fit by international and domestic standards to be issued a medical certificate by Transport Canada (TC). In the event of denial or restriction, individuals have the right to a review by an independent decision-maker with medical expertise/training in marine and/or aviation medicine. This paper presents the results of cases submitted to the Transportation Appeal Tribunal of Canada over 19 yr.METHODS: The Tribunal’s repository of medical records was searched and 112 adjudicated cases were reviewed.RESULTS: Since 2000, 55 (49%) cases were in the aviation sector and, since 2010, 57 (51%) cases were in the marine sector. The mean age of applicants was 49 and 54 yr for seafarers and pilots, respectively. Mental illness, cardiovascular disease, visual, and neurological disease were the most common reasons for a medical certificate restriction/denial. The Tribunal upheld the refusal to issue or renew a medical certificate in 89 (79%) cases and 23 (21%) cases were referred back to TC.CONCLUSIONS: Mental illness is the most frequent diagnosis that precipitates a request. The international literature is sparse on the number, causes, and results of the appeal process. Our findings and the application of the medical standards in Canada are generally comparable with those of the United Kingdom. It was not possible to make more than indirect comparisons to those of the United States.Brooks C, MacDonald C. Medical cases adjudicated by the Transportation Appeal Tribunal of Canada: 2000–2018. Aerosp Med Hum Perform. 2020; 91(2):79–85.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".