Analysis of landing performance and ankle injury in elite British artistic gymnastics using a modified drop land task: A longitudinal observational study
Bibliographic record
Abstract
OBJECTIVES: To determine whether differences in landing force and asymmetry of landing force exist between gymnasts at the time of data collection versus those that subsequently experienced an ankle injury 12-months later. STUDY DESIGN: Prospective longitudinal observational design with baseline measures and 12 month follow up. SETTING: British Gymnastics National Training Centre. PARTICIPANTS: Thirty-two asymptomatic elite level gymnasts from three artistic gymnastic squads (n = 15 senior female, n = 10 junior female and n = 7 senior male). MAIN OUTCOME MEASURES: A modified drop land task was used to quantify measures of landing performance. Peak Vertical Ground Reaction Force (PVGRF) was used to measure landing force. The level of inter-limb asymmetry of landing force was calculated using the Limb Symmetry index (LSI). Other measures included injury incidence and percentage coefficient of variation (% CV). RESULTS: There was no statistical difference for landing force (p = 0.481) and asymmetry of landing force (p = 0.698) when comparing injured and non-injured gymnasts. Most participants (69%) demonstrated inter-limb asymmetry of landing forces. CONCLUSIONS: Our findings observed inter-limb asymmetry of landing force in injured gymnasts, although uninjured gymnasts also exhibited asymmetry of landing force. Both magnitude of landing force and inter-limb asymmetries of landing force failed to identify the risk of ankle injury.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".