A Review of Wilderness Patient Transport – A British Columbian Perspective
Bibliographic record
Abstract
British Columbia is a mountainous province known for wilderness adventure. In B.C., transport of patients injured in the wilderness is conducted by a network of agencies including British Columbia Emergency Health Services, the Canadian Armed Forces, and 80 volunteer Search and Rescue teams. A survey of current literature has been conducted via PubMed search to create a narrative review of subjects relevant to wilderness transport, with a focus on areas of potential improvement. Transport is carried out either by air or ground resources and the decision to use one or the other is based on the patient’s condition and factors at the scene. Even when one method is preferred, the other will likely be involved as well; it is important for both air and ground resources to work together to give the patient the greatest benefit. The time needed for transport is heavily dependent upon the distance from the site of dispatch to the patient, the environment, and the patient’s condition. In B.C., helicopter access to the patient may be through landing, Helicopter External Transport Systems, or winching. The combination of these three methods seen in B.C. is similar to that in the UK. Rescue helicopters in B.C. are staffed by paramedics and, while other systems use physicians, there is no convincing literature that one is superior to the other. Overall B.C.’s system of wilderness transport is comparable to other jurisdictions, but the field would benefit from a more robust body of research.
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.013 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".