Does sex have an independent effect on thermoeffector responses during exercise in the heat?
Bibliographic record
Abstract
Although a number of studies have examined potential differences in temperature regulation between males and females during heat stress, conclusions have remained limited as to whether reported differences are due to confounding physical characteristics or to actual differences in the physiological variables of temperature regulation. Recent observations suggest that sex differences in temperature regulation, particularly in sudomotor activity, go beyond those associated with physical characteristics. Females have recently been shown to have a lower sudomotor activity, as well as a lower thermosensitivity of the response compared to males during exercise performed at a fixed rate of metabolic heat production. Furthermore, sex differences in local and whole-body sudomotor activity are only evident above a certain combination of environmental conditions and rate of metabolic heat production. In contrast, both the onset threshold and thermosensitivity of cutaneous vasodilatation are similar between males and females. In theory, differences in the thermosensitivity of sudomotor activity could be related to either a central (neural activity/integration) and/or peripheral (effector organ) modulation of temperature regulation. Based on recent findings, sex differences in sudomotor activity appear to be mediated peripherally, although a central modulation has yet to be conclusively ruled out. Here we present a brief yet comprehensive review of the current state of knowledge pertaining to sex differences in temperature regulation during exercise in the heat.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".