The effects of 4 weeks of an arginine-based supplement on the gas exchange threshold and peak oxygen uptake
Bibliographic record
Abstract
The purpose of the present study was to examine the effects of the daily administration of an arginine-based supplement for 4 weeks on the gas exchange threshold (GET) and peak oxygen uptake. The study used a double-blind, placebo-controlled design. Forty-one college-aged males (mean age +/- SD = 22.1 +/- 2.4 years) were randomized into either the PLACEBO (n = 20) or ARGININE (n = 21) group. The placebo was microcrystalline cellulose. The ARGININE group ingested 3.0 g of arginine, 300 mg of grape seed extract, and 300 mg of polyethylene glycol. All subjects performed an incremental test to exhaustion on a cycle ergometer prior to supplementation (PRE) and after 4 weeks of supplementation (POST). The GET was determined by using the V-slope method of the carbon dioxide output vs. oxygen uptake relationship. The results indicated that there were significant mean increases (PRE to POST) in GET (4.1%), as well as in carbon dioxide output (4.3%) and power output (5.4%) at the GET for the ARGININE group, but no significant changes for the PLACEBO group (2.5%, 4.3%, and 3.9%, respectively). In addition, there were no significant changes in peak oxygen uptake for the ARGININE (-1.0%) or PLACEBO (-1.5%) groups. These findings supported the use of the arginine-based supplement for increasing GET and the associated power output, but not for increasing peak oxygen uptake during cycle ergometry.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".