Effects of Different Stepwise Reduction Taper Protocols on Cycling Performance
Bibliographic record
Abstract
This study examined the effects of different 7-day taper protocols on simulated 20-km time trials (20TT). Following 3 weeks of baseline training, 11 male cyclists (.VO2max = 4.78 +/- 0.66 L.min-1) were randomly assigned to one of three stepwise reduction tapers in which training volume was reduced by 30% (T30, n = 5), 50% (T50, n = 6), or 80% (T80, n = 6) of baseline training with intensity (85% .VO2max) maintained. Cardiorespiratory measurements were collected every 5 km during the 20TT. Results revealed a significant (5.4%, 0.05) improvement in 20TT performance in the T50 protocol with concomitant increases in .VO2 and O2 pulse. No significant differences were found in T30 or T80. These results showed that a moderate (50%) reduction in weekly training volume appeared to be optimal in terms of enhancing performance. This confirms the contention that proper placement of training volume during tapering, while maintaining exercise intensity, can elicit performance improvements.
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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 | 0.000 |
| 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 | 0.000 | 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".