Effect of Elk Velvet Antler Supplementation on the Hormonal Response to Acute and Chronic Exercise in Male and Female Rowers
Bibliographic record
Abstract
To examine the effects of elk velvet antler supplementation (EVA) combined with training on resting and exercise-stimulated hormonal response, male (n = 25) and female (n = 21) rowers ingested either EVA (560 mg/d) or placebo (PL) during 10 wk of training. VO(2max), 2000 m rowing time, leg and bench press strength were determined before and after 5 and 10 wk of training. Serum hormone levels were measured prior to and 5 and 60 min after a simulated 2000 m rowing race. VO(2max)and strength increased and 2000 m times decreased similarly (P < 0.05) with training. There was no significant difference between the EVA and PL group for any hormonal response. Testosterone (males only) and growth hormone (both genders) were higher 5 min after the simulated race (P < 0.05) but returned to baseline at 60 min. Cortisol was higher 5 and 60 min compared to rest (both genders) (P < 0.05) and was higher 60 min post-exercise following 5 and 10 wk of training. It appears that 10 wk of EVA supplementation does not significantly improve rowing performance nor alter hormonal responses at rest or after acute exercise than training alone.
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.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".