Physiological and Health-Related Adaptations to Low-Volume Interval Training: Influences of Nutrition and Sex
Bibliographic record
Abstract
Interval training refers to the basic concept of alternating periods of relatively intense exercise with periods of lower-intensity effort or complete rest for recovery. Low-volume interval training refers to sessions that involve a relatively small total amount of exercise (i.e. ≤10 min of intense exercise), compared with traditional moderate-intensity continuous training (MICT) protocols that are generally reflected in public health guidelines. In an effort to standardize terminology, a classification scheme was recently proposed in which the term 'high-intensity interval training' (HIIT) be used to describe protocols in which the training stimulus is 'near maximal' or the target intensity is between 80 and 100 % of maximal heart rate, and 'sprint interval training' (SIT) be used for protocols that involve 'all out' or 'supramaximal' efforts, in which target intensities correspond to workloads greater than what is required to elicit 100 % of maximal oxygen uptake (VO2max). Both low-volume SIT and HIIT constitute relatively time-efficient training strategies to rapidly enhance the capacity for aerobic energy metabolism and elicit physiological remodeling that resembles changes normally associated with high-volume MICT. Short-term SIT and HIIT protocols have also been shown to improve health-related indices, including cardiorespiratory fitness and markers of glycemic control in both healthy individuals and those at risk for, or afflicted by, cardiometabolic diseases. Recent evidence from a limited number of studies has highlighted potential sex-based differences in the adaptive response to SIT in particular. It has also been suggested that specific nutritional interventions, in particular those that can augment muscle buffering capacity, such as sodium bicarbonate, may enhance the adaptive response to low-volume interval training.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".