Effects of calcium β-HMB supplementation during training on markers of catabolism, body composition, strength and sprint performance
Bibliographic record
Abstract
Calcium β-hydroxy β-methylbutyrate (HMB) supplementation has been reported to reduce catabolism and promote gains in strength and fat free mass in untrained individuals initiating training. However, the effects of HMB supplementation on strength and body composition alterations during training in athletes is less clear. This study examined the effects of 28-d of calcium HMB supplementation during intense training on markers of catabolism, body composition, strength, and sprint performance. In a double-blind and randomized manner, 28 NCAA division I-A football players were matched-paired and assigned to supplement their diet for 28-d during winter resistance/agility training (~8 hr/wk) with a carbohydrate placebo supplement (P) or the P supplement with 3 g/day of HMB as a calcium salt (HMB). Prior to and following supplementation: dietary records and fasting blood samples were obtained; body composition was determined via DEXA; subjects performed maximal effort bench press, barbell back squat, and power clean isotonic repetition tests; and, subjects performed a repeated cycle ergometer sprint test (12 x 6-s sprints with 30-s rest recovery) to simulate a 12-play drive in football. Results revealed no significant differences between the placebo and HMB supplemented groups in markers of catabolism, muscle/liver enzyme efflux, hematological parameters, body composition, combined lifting volume, or repetitive sprint performance. Results indicate that HMB supplementation (3 g/day) during off-season college football resistance/agility training does not reduce catabolism or provide ergogenic benefit.
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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 | 0.000 | 0.001 |
| 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".