One session of interval work does not alter <i>V</i>O<sub>2max</sub>, peak power or plasma volume
Bibliographic record
Abstract
Abstract We examined the effect of one high‐intensity cycling workout on aerobic capacity (VO2max), peak cycling power, and estimated change in plasma volume on subsequent days. Eight healthy males (age=29.5±5.3 years, height=1.81±0.09 m, mass=81.5±7.5 kg) visited the laboratory on three occasions. The first visit (D1) included baseline measures of cycling VO2max, haematocrit, and haemoglobin. Following a brief rest, the participants performed a high‐intensity cycling workout of six 30‐s cycling intervals (modelled on the Wingate cycle test) with each repetition separated by 3 min rest. The final two visits (D2 and D3) included identical measures as the first visit and occurred 48 and 96 h after the interval workout. No significant differences were found for VO2max (53.4±5.3, 53.7±6.7, and 53.7±6.2 ml · kg−1 · min−1), peak power (386±35, 384±35, and 389±35 W) or estimated change in plasma volume [−0.8±8.5% (D1–D2), 1.5±11.5% (D2–D3), and −1.6±9.6% (D1–D3)] between any of the three test days. Our results show that one short‐term high‐intensity cycling workout does not alter VO2max, peak power or estimated change in plasma volume on subsequent days, and is therefore unlikely to benefit or hinder 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 | 0.000 | 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) | 0.004 | 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".