Following A Sprint Interval Session VCO2 Decreases More Rapidly Than VO2
Bibliographic record
Abstract
We have observed that during a sprint interval training (SIT) session after the first all-out effort, independent of power output, there is a progressive decrease in VCO2, while VO2 and ventilation (VE) remain elevated. However, the effects of a 4-bout SIT session on VO2 and VCO2 during post-exercise recovery remain unclear. PURPOSE: To examine changes in VO2 and VCO2 during the recovery period (both immediate and prolonged) following a SIT session.FigureMETHODS: Eight male recreationally active subjects (age=23±2.3y, ht=181±6.4cm, mass=78±8.6kg; mean+SD) completed an acute SIT session (4, 30s all out cycle efforts; external load=10% body mass, each followed by 4min active recovery; total time=18min). Gas exchange (VO2 and VCO2) was measured prior to (following a 12h overnight fast) and after the SIT session (several times up to 24h). Both breakfast (29 kJ·kg-1; 72%CHO, 15%FAT, 13%PRO) and lunch (46 kJ·kg-1; 55%CHO, 27%FAT, 18%PRO) were provided. RESULTS: Respiratory exchange ratio (RER) was significantly elevated (RER =0.86; P<0.05) from the end of exercise-15min recovery, depressed (RER=0.61; P<0.05) 15-30min recovery post-SIT, and returned to more normal values (RER=0.76) by 2h post-exercise. This decrease in RER was due to a more rapid decrease in VCO2 relative to the decrease in VO2 (Fig). CONCLUSION: For at least 30min following SIT, post-exercise VCO2 decreases more rapidly than VO2, producing abnormally low RER values. Although this may simply reflect increased CO2 storage due to the hyperventilation associated with SIT, the mechanism(s) responsible for these transient fluctuations in RER immediately post-SIT require further study. Supported in part by a UWO Academic Development Fund Award.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".