Eight weeks of pre- and postexercise whey protein supplementation increases lean body mass and improves performance in Division III collegiate female basketball players
Bibliographic record
Abstract
We examined if 8 weeks of whey protein (WP) supplementation improved body composition and performance measures in NCAA Division III female basketball players. Subjects were assigned to consume 24 g WP (n = 8; age, 20 ± 2 years; height, 170 ± 6 cm; weight, 66.0 ± 3.1 kg) or 24 g of maltodextrin (MD) (n = 6; age, 21 ± 3 years; height, 169 ± 6 cm; weight, 68.2 ± 7.6 kg) immediately prior to and following training (4 days/week anaerobic and resistance training) for 8 weeks. Prior to (T1) and 8 weeks following supplementation (T2), subjects underwent dual X-ray absorptiometry body composition assessment as well as performance tests. The WP group gained lean mass from T1 to T2 (+1.4 kg, p = 0.003) whereas the MD group trended to gain lean mass (+0.4 kg, p = 0.095). The WP group also lost fat mass from T1 to T2 (-1.0 kg, p = 0.003) whereas the MD group did not (-0.5 kg, p = 0.41). The WP group presented greater gains in 1-repetition maximum (1RM) bench press (+4.9 kg) compared with the MD group (+2.3 kg) (p < 0.05). Moreover, the WP group improved agility from T1 to T2 (p = 0.001) whereas the MD group did not (p = 0.38). Both groups equally increased leg press 1RM, vertical jump, and broad jump performances. This study demonstrates that 8 weeks of WP supplementation improves body composition and select performance variables in previously trained female 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| 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".