Creatine, Arginine α-Ketoglutarate, Amino Acids, and Medium-Chain Triglycerides and Endurance and Performance
Bibliographic record
Abstract
Creatine (Cr) supplementation increases muscle mass, strength, and power. Arginine a-ketoglutarate (A-AKG) is a precursor for nitric oxide production and has the potential to improve blood flow and nutrient delivery (i.e., Cr) to muscles. This study compared a commercial dietary supplement of Cr, A-AKG, glutamine, taurine, branched-chain amino acids, and medium-chain triglycerides with Cr alone or placebo on exercise performance and body composition. Thirty-five men (approximately 23 yr) were randomized to Cr + A-AKG (0.1 g . kg(-1) . d(-1) Cr + 0.075 g . kg(-1) . d(-1)A-AKG, n = 12), Cr (0.1 g . kg(-1) . d(-1), n = 11), or placebo (1 g . kg(-1) . d(-1) sucrose, n = 12) for 10 d. Body composition, muscle endurance (bench press), and peak and average power (Wingate tests) were measured before and after supplementation. Bench-press repetitions over 3 sets increased with Cr + A-AKG (30.9 +/- 6.6 +/- 34.9 +/- 8.7 reps; p < .01) and Cr (27.6 +/- 5.9 +/- 31.0 +/- 7.6 reps; p < .01), with no change for placebo (26.8 +/- 5.0 +/- 27.1 +/- 6.3 reps). Peak power significantly increased in Cr + A-AKG (741 +/- 112 +/- 794 +/- 92 W; p < .01), with no changes in Cr (722 +/- 138 +/- 730 +/- 144 W) and placebo (696 +/- 63 +/- 705 +/- 77 W). There were no differences in average power between groups over time. Only the Cr-only group increased total body mass (79.9 +/- 13.0 +/- 81.1 +/- 13.8 kg; p < .01), with no significant changes in lean-tissue or fat mass. These results suggest that Cr alone and in combination with A-AKG improves upper body muscle endurance, and Cr + A-AKG supplementation improves peak power output on repeated Wingate tests.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".