The effect of progressive heat acclimation on change in body heat content in young males
Bibliographic record
Abstract
Heat acclimation improves the physiological capacity to dissipate heat. As previous studies have only relied upon core temperature and local heat loss measurements, it remains unclear the extent to which whole‐body heat loss, and therefore body heat storage is altered during heat acclimation. Using direct calorimetry, we examined whole‐body heat exchange during progressive increases in the requirement for heat loss during and following a 14‐day heat acclimation protocol. Six young males (Mean±SD, age: 23±3yrs) performed intermittent exercise (3×30‐min bouts of cycling at 300, 350, and 400 W·m −2 separated by 10 min rest period) in dry heat (35°C, 20% relative humidity [RH]) prior to (day 0), during (day 7), and at the end (day 14) of a 14‐day heat acclimation. On days 1–6 and 8–13, subjects cycled for 90 min (~50% VO 2max ) in the heat (40°C, 20% RH). Despite a similar requirement between test days, significantly lower increases in evaporative heat loss were observed for the final exercise bout in days 0 (P=0.01) and 7 (P=0.02) relative to day 14. After 7 days of acclimation, the ΔH b following the exercise did not significantly decrease from day 0 (673±165 vs. 449±109 kJ, p=0.112). However, on day 14 the ΔH b was significantly reduced compared to day 0 (363±64 vs. 673±165 kJ, p=0.04). These data suggest that 14 days is necessary to achieve sufficient heat acclimation to significantly reduce heat storage during exercise in the heat. Support: Deep Mining Research Consortium (Dr. Glen P. Kenny)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".