Mode of exercise and sex are not important for oxygen consumption during and in recovery from sprint interval training
Bibliographic record
Abstract
Most sprint interval training (SIT) research involves cycling as the mode of exercise and whether running SIT elicits a similar excess postexercise oxygen consumption (EPOC) response to cycling SIT is unknown. As running is a more whole-body-natured exercise, the potential EPOC response could be greater when using a running session compared with a cycling session. The purpose of the current study was to determine the acute effects of a running versus cycling SIT session on EPOC and whether potential sex differences exist. Sixteen healthy recreationally active individuals (8 males and 8 females) had their gas exchange measured over ∼2.5 h under 3 experimental sessions: (i) a cycle SIT session, (ii) a run SIT session, and (iii) a control (CTRL; no exercise) session. Diet was controlled. During exercise, both SIT modes increased oxygen consumption (cycle: male, 1.967 ± 0.343; female, 1.739 ± 0.296 L·min(-1); run: male, 2.169 ± 0.369; female, 1.791 ± 0.481 L·min(-1)) versus CTRL (male, 0.425 ± 0.065 L·min(-1); female, 0.357 ± 0.067; P < 0.001), but not compared with each other (P = 0.234). In the first hour postexercise, oxygen consumption was still increased following both run (male, 0.590 ± 0.065; female, 0.449 ± 0.084) and cycle SIT (male, 0.556 ± 0.069; female, 0.481 ± 0.110 L·min(-1)) versus CTRL and oxygen consumption was maintained through the second hour postexercise (CTRL: male, 0.410 ± 0.048; female, 0.332 ± 0.062; cycle: male, 0.430 ± 0.047; female, 0.395 ± 0.087; run: male, 0.463 ± 0.051; female, 0.374 ± 0.087 L·min(-1)). The total EPOC was not significantly different between modes of exercise or males and females (P > 0.05). Our data demonstrate that the mode of exercise during SIT (cycling or running) is not important to O2 consumption and that males and females respond similarly.
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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) | 0.003 | 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".