Physiological and Performance Adaptations to High-Intensity Interval Training
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High-intensity interval training (HIIT) refers to exercise that is characterized by relatively short bursts of vigorous activity, interspersed by periods of rest or low-intensity exercise for recovery. In untrained and recreationally active individuals, short-term HIIT is a potent stimulus to induce physiological remodeling similar to traditional endurance training despite a markedly lower total exercise volume and training time commitment. As little as six sessions of 'all-out' HIIT over 14 days, totaling ∼15 min of intense cycle exercise within total training time commitment of ∼2.5 h, is sufficient to enhance exercise capacity and improve skeletal muscle oxidative capacity. From an athletic standpoint, HIIT is also an effective strategy to improve performance when supplemented into the already high training volumes of well-trained endurance athletes, although the underlying mechanisms are likely different compared to less trained subjects. Most studies in this regard have examined the effect of replacing a portion (typically ∼15-25%) of base/normal training with HIIT (usually 2-3 sessions per week for 4-8 weeks). It has been proposed that a polarized approach to training, in which ∼75% of total training volume be performed at low intensities, with 10-15% performed at very high intensities may be the optimal training intensity distribution for elite athletes who compete in intense endurance events.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it