Epidemiology of Mountain Search and Rescue Operations in Banff, Yoho, and Kootenay National Parks, 2003–06
Bibliographic record
Abstract
OBJECTIVE: To describe the epidemiology of mountain incidents and mountain rescue operations occurring in Banff, Yoho, and Kootenay National Parks between 1 January 2003 and 31 December 2006. METHODS: Retrospective review of Banff, Yoho, and Kootenay Public Safety Occurrence Reports detailing rescue operations within the study period. Demographics, activity, reason for rescue, mode of rescue, type of injury, and fatalities were analyzed. RESULTS: A total of 317 emergency mountain rescue operations involving 406 persons was documented. The mean age of the rescued population was 35.2 years, and this population was predominantly male (63.1%). Hikers were involved in 43.5% of incidents, and 'slips and falls' were responsible for 50.2%. Helicopter was the mode of rescue in 64% of cases. Almost half (40.7%) of all rescues involved people with no injuries. The limbs were the most common body part affected (68% of traumatic injuries). Forty fatalities occurred-45% due to avalanches and 27.5% due to slips and falls. CONCLUSIONS: This study offers a synopsis of the rescue service provided by Parks Canada Rescue in the study area. Further work is needed to separate primary and contributory causes of mountain incidents, and this can be achieved by use of better data collection methods. Hospital follow-up is required to accurately assess the morbidity and mortality associated with mountain incidents. Data presented are expected to be of value to a variety of tourism, health, and safety organizations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".