Does ipsilateral and bilateral knee strength status predict lower extremity injuries of elite judokas; a prospective cohort study
Bibliographic record
Abstract
The association of pre-participation knee muscle strength status with lower limb injury occurrence was investigated. Knee extensors and flexors muscle strength status including the traditional hamstrings/quadriceps (H/Q), Q/Q, H/H, and the non-dominant H/Q: dominant H/Q, HQ:HQ, ratios were recorded before the 10 month judo activity. Fifteen lower limb sport injuries were recorded for 53 judokas during the follow-up questionnaires. Significant accuracy of dominant H/Q ratio 60º/s (AUC 0.702, 95% CI 0.520 to .883, p = 0.023), as well as HQ:HQ ratios 300º/s (AUC .318, 95% CI 0.138 to 0.497, p = 0.040), and 60 º/s (AUC 0.311, 95% CI 0.130 to 0.491, p = .033) were revealed discriminating between injured and uninjured judokas. The optimum cut-off of dominant H/Q ratio associated with belonging to uninjured judokas group was 43.2% (sensitivity, 0.974; specificity, 0.533). Isokinetic knee muscle dynamometry is useful for predicting the likelihood of lower limb injuries in professional judokas during competitive activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".