Low‐volume high‐intensity interval training for cardiometabolic health
Bibliographic record
Abstract
High-intensity interval training (HIIT) is characterised by short bouts of high-intensity submaximal exercise interspersed with rest periods. Low-volume HIIT, typically involving less than 15 min of high-intensity exercise per session, is being increasingly investigated in healthy and clinical populations due to its time-efficient nature and purported health benefits. The findings from recent trials suggest that low-volume HIIT can induce similar, and at times greater, improvements in cardiorespiratory fitness, glucose control, blood pressure, and cardiac function when compared to more traditional forms of aerobic exercise training including high-volume HIIT and moderate intensity continuous training, despite requiring less time commitment and lower energy expenditure. Although further studies are required to elucidate the precise mechanisms of action, metabolic improvements appear to be driven, in part, by enhanced mitochondrial function and insulin sensitivity, whereas certain cardiovascular improvements are linked to increased left ventricular function as well as greater central and peripheral arterial compliance. Beyond the purported health benefits, low-volume HIIT appears to be safe and well-tolerated in adults, with high rates of reported exercise adherence and low adverse effects.
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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) | 0.010 | 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".