Epidemiological Trends in Search and Rescue Incidents Documented by the Alpine Club of Canada From 1970 to 2005
Bibliographic record
Abstract
OBJECTIVE: To provide a descriptive review of the epidemiology of search and rescue (SAR) incidents across Canada as documented in the Alpine Club of Canada (ACC) database. METHODS: A retrospective, cross-sectional review of SAR reports collected by the ACC with incidents dating from January 1, 1970 to June 12, 2005, was analyzed. RESULTS: The ACC database contained 1088 incidents with 1377 casualties. Casualties had 944 (68.6%; 95% CI, 64.2 to 73.1) injuries or illness, and 433 (31.4%; 95% CI, 28.6 34.6) fatalities. Males accounted for 76.1% of all casualties and 82.3% of the fatalities when sex was reported. A bimodal distribution of casualties was seen, with the peaks around February and August. Hiking and mountaineering resulted in more than half of all casualties that yielded any type of morbidity, whereas mountaineering and skiing, ski mountaineering, or snowboarding accounted for almost two thirds of all fatalities. Human error and slips and falls were the major contributors to the presumptive cause of incidents. The lower limb was the most common anatomic location of traumatic injury, accounting for 41.6% (95% CI, 37.6 to 45.9) of these injuries. Hypothermia, exhaustion, frostbite, and dehydration represented the majority of all nontraumatic conditions. British Columbia and Alberta accounted for 91.6% (95% CI, 86.0 to 97.5) of the incidents in the database. CONCLUSIONS: The study serves to illustrate trends in SAR epidemiology that may be encountered by SAR personnel within British Columbia and Alberta. Furthermore, it highlights the need for additional Canadian-based studies to better understand this area of prehospital medical encounters.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".