Bilateral difference between lower limbs in children practicing laterally dominant vs. non‐laterally dominant sports
Bibliographic record
Abstract
ABSTRACT Bilateral asymmetry in lower‐limb power and dynamic balance has been associated with increased risk of sport injury, whereas there is a lack of research examining this asymmetry for child athletes. Twenty‐eight fencers (19 boys and 9 girls, aged 9.71 ± 1.08 years) and 28 Taekwondo athletes (19 boys and 9 girls, aged 9.71 ± 1.08 years) were examined on the single‐leg jump and Star Excursion Balance Test (SEBT) performance. A mixed model design ANOVA (2 [Sex: Boys, Girls] × 2 [Sport group: Fencing, Taekwondo] × 2 [Limb: Dominant, Non‐dominant Leg]) was conducted to examine for difference for each test. There was a significant main effect of limb on hop and triple hop distance (p < 0.05). A significant limb by sex interaction (p = 0.000) was shown for the single‐leg countermovement jump (CMJ) performance, wherein a bilateral difference was only shown in boys. In SEBT, a main effect (p = 0.007) of limb was identified for posterolateral (PL) reach distance. A limb by sex interaction (p = 0.009) was also shown for posteromedial (PM) reach distance, wherein a bilateral difference was only shown in girls. These findings suggest that child athletes in both laterally dominant and non‐laterally dominant sports showed inter‐limb asymmetry of leg power and dynamic balance. Sex should be an important consideration when evaluating bilateral difference of leg power and dynamic balance for child athletes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.006 | 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".