Prior heavy-intensity exercise speeds V<scp>o</scp><sub>2</sub> kinetics during moderate-intensity exercise in young adults
Bibliographic record
Abstract
The effect of prior heavy-intensity warm-up exercise on subsequent moderate-intensity phase 2 pulmonary O2 uptake kinetics (tauVO2) was examined in young adults exhibiting relatively fast (FK; tauVO2 < 30 s; n = 6) and slow (SK; tauVO2 > 30 s; n = 6) VO2 kinetics in moderate-intensity exercise without prior warm up. Subjects performed four repetitions of a moderate (Mod1)-heavy-moderate (Mod2) protocol on a cycle ergometer with work rates corresponding to 80% estimated lactate threshold (moderate intensity) and 50% difference between lactate threshold and peak VO2 (heavy intensity); each transition lasted 6 min, and each was preceded by 6 min of cycling at 20 W. VO2 and heart rate (HR) were measured breath-by-breath and beat-by-beat, respectively; concentration changes of muscle deoxyhemoglobin (HHb), oxyhemoglobin, and total hemoglobin were measured by near-infrared spectroscopy (Hamamatsu NIRO 300). tauVO2 was lower (P < 0.05) in Mod2 than in Mod1 in both FK (20 +/- 5 s vs. 26 +/- 5 s, respectively) and SK (30 +/- 8 s vs. 45 +/- 11 s, respectively); linear regression analysis showed a greater "speeding" of VO2 kinetics in subjects exhibiting a greater Mod1 tauVO2. HR, oxyhemoglobin, and total hemoglobin were elevated (P < 0.05) in Mod2 compared with Mod1. The delay before the increase in HHb was reduced (P <0.05) in Mod2, whereas the HHb mean response time was reduced (P <0.05) in FK (Mod2, 22 +/- 3 s; Mod1, 32 +/- 11 s) but not different in SK (Mod2, 36 +/- 13 s; Mod1, 34 +/- 15 s). We conclude that improved muscle perfusion in Mod2 may have contributed to the faster adaptation of VO2, especially in SK; however, a possible role for metabolic inertia in some subjects cannot be overlooked.
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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 | 0.000 |
| 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".