The Effect of Postexercise Milk Protein Intake on Rehydration of Children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: In adults, rehydration after exercise in the heat can be enhanced with a protein-containing beverage; however, whether this applies to children remains unknown. This study examined the effect of milk protein intake on postexercise rehydration in children. METHOD: Fifteen children (10-12 years) performed three exercise trials in the heat (34.4 ± 0.2 °C, 47.9 ± 1.1% relative humidity). In a randomized, counterbalanced crossover design, participants consumed iso-caloric and electrolyte-matched beverages containing 0 g (CONT), 0.76 g (Lo-PRO) or 1.5 g (Hi-PRO) of milk protein/100 mL in a volume equal to 150% of their body mass (BM) loss during exercise. BM was then assessed over 4 h of recovery. RESULTS: Fluid balance demonstrated a significant condition × time interaction (p = .012) throughout recovery; Hi-PRO was less negative than CONT at 2 hr (p = .01) and tended to be less negative at 3 h (p = .07). Compared with CONT, beverage retention was enhanced by Hi-PRO at 2 h (p < .05). CONCLUSION: A postexercise beverage containing milk protein can favorably affect fluid retention in children. Further research is needed to determine the optimal volume and composition of a rehydration beverage for complete restoration of fluid balance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it