Immersion with menthol improves recovery between 2 cycling exercises in hot and humid environment
Bibliographic record
Abstract
Endurance exercise performance is impaired in a hot and humid environment. This study compared the effects of cold water immersion, with (CMWI) and without (CWI) menthol, on the recovery of cycling performance. Eight heat-acclimatized cyclists (age, 24.1 ± 4.4 years; mass, 65.3 ± 5.2 kg) performed 2 randomized sessions, each consisting of a 20-min cycling trial (T1) followed by 10 min of immersion during recovery and then a second 20-min cycling trial (T2). Mean power output and perceived exertion (RPE) were recorded for both trials. Rectal (Trec) and skin temperatures were measured before and immediately after T1, immersion, and T2. Perceived thermal sensation (TS) and comfort were measured immediately after T1 and T2. Power output was significantly improved in T2 compared with T1 in the CMWI condition (+15.6%). Performance did not change in the CWI condition. After immersion, Trec was lower in CWI (–1.17 °C) than in CMWI (–0.6 °C). TS decreased significantly after immersion in both conditions. This decline was significantly more pronounced in CMWI (5.9 ± 1 to 3.6 ± 0.5) than in CWI (5.6 ± 0.9 to 4.4 ± 1.2). In CMWI, RPE was significantly higher in T1 (6.57 ± 0.9) than in T2 (5.14 ± 1.25). However, there was no difference in TC. This study suggests that menthol immersion probably (i) improves the performance of a repeated 20-min cycling bout, (ii) decreases TS, and (iii) impairs thermoregulation processes.
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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) | 0.000 | 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 | 0.000 |
| 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".