Effect of a 3-Weeks Training Camp on Muscle Oxygenation, V˙O2 and Performance in Elite Sprint Kayakers
Bibliographic record
Abstract
Purpose Peripheral adaptations, as assessed via near-infrared spectroscopy (NIRS) derived changes in muscle oxygenation (SmO2), are good predictors of sprint kayak performance. Therefore, the goal of the present study was to assess changes in SmO2 and V̇O2 following a training camp in elite sprint kayakers to evaluate if the training prescribed elicits peripheral adaptations, and to assess associations between training-induced changes in physiological responses and performance. Methods Eight male elite sprint kayakers, members of the Canadian National Team, performed a 200-m and 1000-m on-water time trial (TT) before and after a 3-week winter training camp. Change in performance, V̇O2 and SmO2 of the biceps brachii were assessed in relation to training load. Results Training load and intensity were increased by ~20% over the course of the training camp, which resulted in a 3.7±1.7% (ES -1.2) and 2.8±2.4% (ES -1.3) improvement in 200-m and 1000-m performance, respectively. Performance improvement in the 200-m was concomitant to a reduced SmO2, an increased V̇O2peak and an increased reoxygenation rate after the TT. The 1000-m TT performance improvement was concurrent with a reduced SmO2 in the last half of the TT and an increased V̇O2 in the first minute of the TT. Conclusion Our results strongly suggest that peripheral skeletal muscle adaptations occurred in these athletes with the proposed training plan. This further attests the benefit of using portable NIRS as a monitoring tool to track training-induced adaptations in muscle oxygen extraction in elite athletes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".