Steady‐state local sweat rate is determined by the evaporation required for heat balance relative to body surface area (1104.9)
Bibliographic record
Abstract
Recent evidence suggests whole‐body sweat rate (WBSR, g·min –1 ) is determined by the absolute evaporation required for heat balance (E req , W). However, since differences in body surface area (BSA) should theoretically modify local sweat rate (LSR, mg·cm –2 ·min –1 ) for a given absolute E req , we hypothesized that LSR is determined by E req relative to BSA (W·m –2 ) rather than absolute E req (W). Sixteen males of large (L: 2.12±0.09 m 2 , n=8) and small (S: 1.80±0.09 m 2 , n=8) BSA cycled in 25°C at workloads eliciting E req of 340 and 400 W, and 165 and 190 W·m –2 . Heat production was estimated via indirect calorimetry. WBSR was estimated from changes in body mass between 45 and 60 min, and LSR was taken as the mean of back and forearm ventilated capsule measurements from 45‐60 min. WBSR was similar between groups at 340 and 400 W (p蠅0.54), but LSR was greater at 400 W (p=0.03), and 340 W (p=0.07), in S. At 165 and 190 W·m –2 , no differences in LSR were evident (p蠅0.86), while WBSR was greater in L at 165 W·m –2 (p=0.01) but not at 190 W·m –2 (p=0.13). Differences in BSA modify LSR for a given absolute E req , while the prescription of E req in W·m –2 results in similar LSR irrespective of BSA. Grant Funding Source : Supported by a NSERC Discovery Grant (O. Jay)
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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) | 0.002 | 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".