Pattern of Injury and Illness During Expedition-Length Adventure Races
Bibliographic record
Abstract
OBJECTIVE: To describe injuries and illnesses treated during an expedition-length adventure race and combine the results with those from previous studies to identify common patterns of injury and illness during these events. METHODS: The 2003 Subaru Primal Quest Expedition Length Adventure Race was held in Lake Tahoe, CA, from September 5 to 14, 2003. Eighty teams of 4 individuals participated. During the event, medical volunteers providing on-site medical care recorded each medical encounter on a medical encounter form. This information was used to describe the injuries and illnesses treated and was combined with previous investigations to identify common patterns of injury and illness during these events. RESULTS: During the 10-day study period, 356 patient encounters and 406 injuries and illnesses were recorded. The most frequent reason to require on-site medical care was injury of the skin and soft tissue (70.4%), with blisters the single most common of these injuries (45.6%). Other reasons were orthopedic injury (14.8%), respiratory illness (3.7%), and heat illness or dehydration (3.7%). CONCLUSIONS: The results of this and previous studies demonstrate a common pattern of injury and illness that includes a high frequency of skin and soft tissue injury, especially blisters. Injuries and illnesses such as altitude illness, contact dermatitis, and respiratory illness varied considerably among events. The number of patient encounters per athlete is similar among the studies, providing an approximation of the number of medical encounters expected given the number of participants. These results should assist medical providers for future events; however, it is imperative to carefully review the individual event to best predict the frequency of injury and illness.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".