Internet-based survey of the nature and perceived causes of injury to dogs participating in agility training and competition events
Bibliographic record
Abstract
OBJECTIVE: To characterize injuries (on the basis of type and severity of injury and affected region of the body) among dogs participating in agility training and competition events and examine associations between injury characteristics and perceived causes of injury. DESIGN: Internet-based, retrospective, cross-sectional survey. ANIMALS: 3,801 privately owned dogs participating in agility training or trials. PROCEDURES: A retrospective electronic survey was developed to investigate demographic factors for dogs and handlers, frequency of participation in agility training and competition, and perceived causes and characteristics of injuries acquired by dogs during agility-related activities. Respondents were handlers recruited through member lists of large canine agility associations in Canada and the United Kingdom and through promotion on an agility blog site. Associations between cause and anatomic site or type of injury and between injury severity (mild vs severe) and setting (competition vs practice) were investigated. RESULTS: Surveys were received from 1,669 handlers of 3,801 agility dogs internationally. Handler-reported data indicated 1,209 of 3,801 (32%) dogs had ≥ 1 injury; of 1,523 analyzed injuries, the shoulder (349 injuries), back (282), and neck (189) regions and phalanges (202) were predominantly affected. Soft tissue injuries (eg, strain [muscle or tendon injury; 807], sprain [ligament injury; 312], and contusion [200]) were common. Injuries were most commonly incurred during interactions with bar jumps, A-frames, and dog walk obstacles (260, 235, and 177 of 1,602 injuries, respectively). Anatomic site and type of injury were significantly associated with perceived cause of injury. CONCLUSIONS AND CLINICAL RELEVANCE: These findings provided a basis for further experimental studies to identify specific mechanisms of various types of injury in dogs that participate in agility activities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".