A Retrospective Survey of Injuries Occurring in Dogs and Handlers Participating in Canicross
Bibliographic record
Abstract
OBJECTIVES: Canicross is a popular canine and human cross-country sport. The purpose of this study was to identify the most common injuries, their severity, risk factors and the recovery. METHODS: An internet-based retrospective survey design was used to examine the characteristics of injuries, demographic and competition information and associations with injury rate. RESULTS: A total of 160 surveys were received and indicated that at the time of the survey 21.9% of dogs (35/160) had experienced at least one injury. Lacerations, abrasions and punctures were the most common injury type (22/49), most frequently occurring in the footpads of the forelimb (13/16). The majority of dogs (38/49) recovered from their injuries. Sixty-nine out of 147 of the human handlers experienced injuries while competing; ankle injuries (25/69) and bruises, cuts and grazes (20/69) were the most common injuries. Risk factors for injuries were being a purebred Labrador, dogs running with another dog and additionally competing in agility. CONCLUSIONS: Labradors, dogs running with another dog and dogs also participating in agility competitions were at higher risk for injury. Injuries of the footpads of the forelimb were the most common injuries in dogs. Most dogs had a complete recovery from their injuries. CLINICAL SIGNIFICANCE: This is the first study that gives us insight into injuries occurring in dogs and handlers competing in canicross. This will help making recommendations for this sport as well as enable veterinarians to understand the risks and injuries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".