Regional variation in the reliability of sweat rate measured via the ventilated capsule technique during passive heating
Bibliographic record
Abstract
Abstract The ventilated capsule technique is widely used to measure time‐dependent changes in sweating in humans. However, evaluations of its reliability (consistency) have been restricted to the forearm, despite extensive regional heterogeneity in the sweating response. Given the importance of such information for experimental design, statistical analysis and interpretation, we determined the reliability of local sweat rate at nine sites during whole‐body passive (resting) heating. On three separate occasions, a water‐perfused suit was used to increase and clamp oesophageal temperature 0.6, 1.2 and 1.8°C above baseline in 14 young men [24 (SD 5) years of age], while sweat rate was measured at the forehead, chest, abdomen, biceps, forearm, hand, quadriceps, calf and foot using ventilated capsules (3.8 cm2). Absolute and relative reliability were determined via the coefficient of variation (CV) and intraclass correlation coefficient (ICC), respectively. At low heat strain (0.6°C), almost all sites had acceptable relative reliability (ICC ≥ 0.70) and moderate absolute reliability (CV < 25%). At moderate heat strain (1.2°C), only the abdomen, hand, quadriceps and foot had acceptable relative reliability, whereas the forehead, abdomen, forearm, hand and quadriceps had moderate absolute reliability. At high heat strain (1.8°C), relative reliability was acceptable at the abdomen, quadriceps, calf and foot, whereas the chest, abdomen, forearm, hand, quadriceps, calf and foot had moderate absolute reliability. Our findings indicate that the measurement site and level of heat strain impact the consistency of local sweat rate measured via the ventilated capsule technique, and we demonstrate the possible implications for research design and data interpretation.
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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 | 0.002 | 0.007 |
| 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".