Effect of carbohydrate beverage ingestion on central versus peripheral fatigue: a placebo-controlled, randomized trial in cyclists
Bibliographic record
Abstract
We investigated whether carbohydrate ingestion delays fatigue in endurance-trained cyclists via peripheral or central mechanisms. Ten men (35 ± 9 years of age) and 10 women (42 ± 7 years of age) were assigned, in a double-blind, crossover design, to a sports drink (CHO) or to a placebo (PL). The following strength measures were made 3 times (before exercise, after a time trial (TT), and after a ride to exhaustion): (i) maximal voluntary contraction (MVC); (ii) MVC with superimposed femoral nerve magnetic stimulation to measure central activation ratio (CAR); and (iii) femoral nerve stimulation in a 3-s pulse train on relaxed muscle. The subjects cycled for 2 h at approximately 65% of peak oxygen consumption, with five 1-min sprints interspersed, followed by a 3-km TT. After strength testing, the cyclists remounted their bikes, performed a brief warm-up, and pedaled at approximately 85% peak oxygen consumption until unable to maintain workload. Changes in metabolic and strength measurements were analyzed with repeated-measures ANOVA. From before exercise to after the TT, MVC declined in men (17%) and women (18%) (p = 0.004), with no effect of beverage (p > 0.193); CAR decreased in both sexes with PL (p = 0.009), and the decline was attenuated by CHO in men only (time × treatment, p = 0.022); and there was no evidence of peripheral fatigue in either sex with either beverage (p > 0.122). Men rode faster in the TT with CHO (p = 0.005) but did not improve performance in the ride to exhaustion (p = 0.080). In women, CHO did not improve performance in the TT (p = 0.173) or in the ride to exhaustion (p = 0.930). We concluded that carbohydrate ingestion preserved central activation and performance in men, but not in women, during long-duration cycling.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".