SIX BOUTS OF SPRINT INTERVAL TRAINING (SIT) IMPROVES INTENSE AEROBIC CYCLING PERFORMANCE AND PEAK ANAEROBIC POWER
Bibliographic record
Abstract
Two weeks of SIT increased maximal aerobic power (VO2peak), however maximal anaerobic power (Wmax; 30-sec ‘all out’ Wingate test) was unaffected, possibly due to chronic fatigue induced by 14 daily training bouts (Roads et al. Eur. J. Appl. Physiol. 82:480–86, 2000). The effect of fewer sprint training bouts on these parameters is unknown, and no study has assessed changes in performance or skeletal muscle metabolism during intense aerobic exercise after SIT. PURPOSE We examined whether 6 bouts of SIT, performed over 2 wks with 1–2 d rest between bouts, elicited changes in VO2peak, Wmax, or performance/metabolism during a ‘challenge ride’ to exhaustion @ −80% VO2peak. METHODS 8 recreationally-active subjects [6 men; 23±2 yr (mean±SD)] were studied before and 2–3 d following the SIT protocol (6 bouts × 4–8 Wingate tests with 4 min recovery between tests). RESULTS VO2peak was unchanged by SIT (Post: 45.5±5.0 vs. Pre: 44.6±3.2 ml/kg/min) however Wmax increased by 14% (Post: 1067±234 vs Pre: 934±174 W; p ≤ 0.05). Most strikingly, cycle time to exhaustion increased by 101% after SIT (Post: 51.1±30.8 vs. Pre: 25.4±14.4 min, p ≤ 0.01). Biopsies obtained during the challenge rides revealed that muscle lactate ([La]) was not different at rest or after 1 (Post: 23±9 vs Pre: 22±8 mmol/kg dry wt.) or 15 min of exercise (Post: 53±15 vs Pre: 56±13). Extensive metabolic and cardiovascular analyses are underway in order to elucidate potential mechanisms responsible for the marked changes in aerobic performance. CONCLUSION 6 bouts of SIT (total training time: ∼15 min) dramatically improved intense aerobic cycling performance, however this was unrelated to changes in muscle [La] during exercise. Support: NSERC, Canada (MJG) and a Gatorade Sports Science Institute Award (SCH).
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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) | 0.001 | 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) | 0.002 | 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".