A single mega dose of vitamin D<sub>3</sub> improves selected physical variables in vitamin D-deficient young amateur soccer players: a randomized controlled trial
Bibliographic record
Abstract
This randomized controlled trial aimed to test whether vitamin D (VD) supplementation affects measures of physical performance in VD-deficient, mildly trained children. Thirty-six recreationally soccer player boys were randomly assigned to single dose (200 000 IU) of VD3 (n = 19) or placebo (n = 17). Plasma 25-hydroxyvitamin D (25-OHD) was assessed and measures of physical performance (i.e., vertical and standing broad jumps, triple hop, 10-m and 30-m sprints, shuttle run) were performed before and 12 weeks after the loading dose. Mixed ANCOVA models were performed and effect size was estimated by partial eta squared (ηp2). Baseline 25-OHD and physical variables were equivalent in the 2 groups. Twelve weeks after VD loading, plasma 25-OHD increased and physical variables improved only in the VD group. There was a significant interaction effects for group by time for vertical jump (F = 14.9, p = 0.001, ηp2 = 0.394), triple hop jump (F = 24.2, p < 0.001, ηp2 = 0.513), 10-m (F = 4.46, p = 0.046, ηp2 = 0.162) and 30-m (F = 6.56, p = 0.017, ηp2 = 0.222) sprints, and shuttle run (F = 13.4, p = 0.001, ηp2 = 0.369). In conclusion, a single bolus of VD3 resulted in significant improvements in jumping ability, agility, and running speed in mildly trained children that are deficient in VD. The findings suggest that correcting VD deficit might be beneficial for physical performance. Novelty A mega dose of VD3 improves jumping ability, agility, and running speed in VD-deficient, mildly trained children. Effect of VD on measures of physical performance is noticeable 3 months after the loading dose.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".