Less is more: standard warm-up causes fatigue and less warm-up permits greater cycling power output
Bibliographic record
Abstract
The traditional warm-up (WU) used by athletes to prepare for a sprint track cycling event involves a general WU followed by a series of brief sprints lasting ≥ 50 min in total. A WU of this duration and intensity could cause significant fatigue and impair subsequent performance. The purpose of this research was to compare a traditional WU with an experimental WU and examine the consequences of traditional and experimental WU on the 30-s Wingate test and electrically elicited twitch contractions. The traditional WU began with 20 min of cycling with a gradual intensity increase from 60% to 95% of maximal heart rate; then four sprints were performed at 8-min intervals. The experimental WU was shorter with less high-intensity exercise: intensity increased from 60% to 70% of maximal heart rate over 15 min; then just one sprint was performed. The Wingate test was conducted with a 1-min lead-in at 80% of optimal cadence followed by a Wingate test at optimal cadence. Peak active twitch torque was significantly lower after the traditional than experimental WU (86.5 ± 3.3% vs. 94.6 ± 2.4%, P < 0.05) when expressed as percentage of pre-WU amplitude. Wingate test performance was significantly better (P < 0.01) after experimental WU (peak power output = 1,390 ± 80 W, work = 29.1 ± 1.2 kJ) than traditional WU (peak power output = 1,303 ± 89 W, work = 27.7 ± 1.2 kJ). The traditional track cyclist's WU results in significant fatigue, which corresponds with impaired peak power output. A shorter and lower-intensity WU permits a better performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".