Differences between Sexes in Rectal Cooling Rates after Exercise-Induced Hyperthermia
Bibliographic record
Abstract
PURPOSE: We evaluated differences between sexes in core cooling rates during cold water immersion after exercise-induced hyperthermia. METHODS: Ten male (M) and nine female (F) participants, matched for body surface area-to-mass ratio (AD/M) (F: 268 +/- 19 vs M: 261 +/- 16 cm2 x kg(-1)), were recruited for the study. Participants exercised until rectal temperature reached 39.5 degrees C and were subsequently immersed in a 2.0 degrees C circulated water bath until rectal temperature decreased to 37.5 degrees C. Rectal and mean skin temperatures and the relative rate of nonevaporative heat loss (W x m(-2)) were measured continuously during the immersion period. RESULTS: Males were heavier, had a lower body fat percentage, and had a greater amount of lean body mass compared with females (P < or = 0.05). Significant differences were found in the overall cooling rate for rectal temperature (F: 0.22 +/- 0.07 vs M: 0.12 +/- 0.03 degrees C x min(-1), P = 0.001) and in the overall immersion times (F: 10.89 +/- 4.49 vs M: 18.13 +/- 4.47 min, P = 0.003). Mean skin temperature was lower in females compared with that in males during the immersion period (P < 0.001), although there were no differences between sexes in the rate of nonevaporative heat loss (P = 0.180). CONCLUSIONS: Although females had a similar AD/M and greater body adiposity, they had approximately 1.7-fold greater rectal cooling rate. Because AD/M and body adiposity do not seem to influence rectal cooling rates in previously hyperthermic individuals, the greater cooling rates in females may be attributed to physical differences in lean body mass.
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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) | 0.000 | 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".