Is There an Association Between Injury History and Lower Extremity Joint Injury During Canada Games Competition?
Why this work is in the frame
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Bibliographic record
Abstract
Background Injuries during elite level competition like the Canada Games, occur frequently and injury history is one of the strongest predictors of future injury; however, this association is unknown in the Canada Games. Purpose To determine the association between injury history and incidence of lower extremity joint injury during Canada Games competition. Methods Data from the 2009 – 2019 Canada Games (8710 male and 8391 female athletes) competitions were de-identified by the Canada Games Council for analysis. Injury data were cleaned and categorized for previous injury and injury type and location. Injury history was self-reported and included concussion, major surgical procedure, neck and back, trauma to joint or bone, and trauma to ligament or tendon. Injury from the Canada Games competitions were categorized to include ankle, knee, hip, and patellofemoral joint injuries. Chi-Square (χ 2 ) test of independence determined association between injury history and incidence of lower extremity joint injury during Canada Games competition. IBM SPSS (Version 26) was used for statistical analysis ( p -value < 0.05). Results Four hundred and seventy-five ankle, 503 knee, 253 hip, and 106 patellofemoral joint injuries were reported during 10 years of Canada Games competitions. There were significant associations between history of neck and back injuries with ankle injuries and knee injuries, history of trauma and overuse of ligament or tendon with hip injuries and history of trauma or overuse of joint or bone with patellofemoral joint injuries. Conclusion These findings support previous literature suggesting that injury history is associated with future injury. Level of Evidence 3
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it