Unilateral Elbow Flexion and Leg Press Training Induce Cross–Education But Not Global Training Gains in Children
Bibliographic record
Abstract
PURPOSE: Whereas cross-education has been extensively investigated with adults, there are far fewer youth investigations. Two studies suggested that children had greater global responses to unilateral knee extensor fatigue and training, respectively, than adults. The objective of this study was to compare global training responses and cross-education effects after unilateral elbow flexion (EFlex) and leg press (LP) training. METHODS: Forty-three prepubertal youths (aged 10-13 y) were randomly allocated into dominant LP (n = 15), EFlex (n = 15) training groups, or a control (n = 13). Experimental groups trained 3 times per week for 8 weeks and were tested pretraining and posttraining for ipsilateral and contralateral 1-repetition maximum LP; knee extensor, knee flexors, elbow flexors; and handgrip maximum voluntary isometric contractions (MVIC), and countermovement jump. RESULTS: In comparison to no significant changes with the control group, dominant elbow flexors training demonstrated significant ( P < .001) improvements only with ipsilateral and contralateral upper body testing (EFlex MVIC [15.9-21.5%], EFlex 1-repetition maximum [22.9-50.8%], handgrip MVIC [5.5-13.8%]). Dominant LP training similarly exhibited only significant ( P < .001) improvements for ipsilateral and contralateral lower body testing (LP 1-repetition maximum [59.6-81.8%], knee extensor MVIC [12.4-18.3%], knee flexor MVIC [7.9-22.3%], and countermovement jump [11.1-18.1%]). CONCLUSIONS: The ipsilateral and contralateral training adaptations in youth were specific to upper or lower body training, respectively.
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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 | 0.000 |
| 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) | 0.002 | 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".