Aeromedical evacuations in the Canadian North: does the presence of a physician alter rates?
Bibliographic record
Abstract
Patients in Nunavut rely exclusively on airplane to access medical care beyond the nursing stations in communities. This can take the form of scheduled flights for chronic and non-urgent issues or dedicated medevacs for emergencies. Each community is routinely visited by family physicians (FP) who provide in-person primary care. The frequency and duration of FP visits depends on the community size, with larger communities having longer and more frequent visits. During their visits, FPs can be called upon to assist in emergencies. This study provides a detailed portrait of the territory's medical travels between 2012 and 2018. Contrary to our initial hypothesis, we show that the presence or absence of an FP in the community did not have a significant impact on the rates of medevacs. However, we found that the rates of non-urgent scheduled flights increased. Our findings provide in-depth information on the rates of medevacs and non-urgent travel in Nunavut. They also raise important questions for primary care in remote areas by demonstrating an increase in routine travel requirements when physicians are present in those communities. As health outcomes were not assessed, further studies are required before recommendations can be made to change the rate of FP visits.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".