The Effect of Wrist Guard Use on Upper-Extremity Injuries in Snowboarders
Bibliographic record
Abstract
The objective of this investigation was to determine the effect of wrist guard use on all upper-extremity injuries in snowboarders. This matched case-control study was conducted at 19 ski areas in Quebec, Canada. Cases were 1,066 injured snowboarders who reported upper-extremity injuries to the ski patrol during the 2001-2002 season. Controls were 970 snowboarders with non-upper-extremity injuries who were matched to cases on ski area and the nearest date, age, and sex, in that order. The response rate was 71.8% (73.5% for cases and 70.1% for controls). Cases were compared with controls with regard to wrist guard use. The prevalence of wrist guard use among snowboarders with hand, wrist, or forearm injuries was 1.6%; for those with elbow, upper arm, or shoulder injuries, it was 6.3%; and for controls, it was 3.9%. Thus, wrist guard use reduced the risk of hand, wrist, or forearm injury by 85% (adjusted odds ratio = 0.15, 95% confidence interval: 0.05, 0.45). However, the adjusted odds ratio for elbow, upper arm, or shoulder injury was 2.35 (95% confidence interval: 0.70, 7.81). These results provide evidence that use of wrist guards reduces the risk of hand, wrist, and forearm injuries but may increase the risk of elbow, upper arm, and shoulder injuries.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".