Effects of a low- or a high-carbohydrate diet on performance, energy system contribution, and metabolic responses during supramaximal exercise
Bibliographic record
Abstract
The purpose of the present study was to examine the effects of a high- or low-carbohydrate (CHO) diet on performance, aerobic and anaerobic contribution, and metabolic responses during supramaximal exercise. Six physically-active men first performed a cycling exercise bout at 115% maximal oxygen uptake to exhaustion after following their normal diet for 48 h (∼50% of CHO, control test). Seventy-two hours after, participants performed a muscle glycogen depletion exercise protocol, followed by either a high- or low-CHO diet (∼70 and 25% of CHO, respectively) for 48 h, in a random, counterbalanced order. After the assigned diet period (48 h), the supramaximal cycling exercise bout (115% maximal oxygen consumption) to exhaustion was repeated. The low-CHO diet reduced time to exhaustion when compared with both the control and the high-CHO diet (-19 and -32%, respectively, p < 0.05). The reduced time to exhaustion following the low-CHO diet was accompanied by a lower total aerobic energy contribution (-39%) compared with the high-CHO diet (p < 0.05). However, the aerobic and anaerobic energy contribution at the shortest time to exhaustion (isotime) was similar among conditions (p > 0.05). The low-CHO diet was associated with a lower blood lactate concentration (p < 0.05), with no effect on the plasma concentration of insulin, glucose and K(+) (p > 0.05). In conclusion, a low-CHO diet reduces both performance and total aerobic energy provision during supramaximal exercise. As peak K(+) concentration was similar, but time to exhaustion shorter, the low-CHO diet was associated with an earlier attainment of peak plasma K(+) concentration.
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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) | 0.000 | 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 | 0.001 |
| 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".