Heat production per unit mass determines the core temperature response to exercise in compensable conditions
Bibliographic record
Abstract
We hypothesized that the change in core temperature during exercise in compensable conditions is determined by heat production per unit mass (W/kg), and not absolute heat production (W) or the percentage of peak oxygen uptake (%VO 2peak ). Nine heat‐acclimated males of high (HI: 89.1±6.3 kg, n=6) or low (LO: 67.2±5.7 kg, n=3) body mass cycled at 500 W, 6.5 W/kg, and 9.0 W/kg in 25°C, as well as 9.0 W/kg in 35°C. Heat production was estimated using indirect calorimetry, and rectal temperature (T re ) was measured throughout. At 500 W (HI: 5.7±0.1 W/kg, LO: 7.3±0.2 W/kg; p<0.001), the change in T re (ΔT re ) was greater in LO (HI: 0.51±0.06°C, LO: 0.96±0.10°C; p=0.007) despite similar %VO 2peak (HI: 45±3%, LO: 47±1%; p=0.573). At all W/kg, ΔT re was not different between groups, yet %VO 2peak was greater in HI at 6.5 W/kg (HI: 50±3%, LO: 42±1%) and 9.0 W/kg (HI: 67±2%, LO: 57±3%). A similar ΔT re was observed within each group at 9.0 W/kg in 25°C and 35°C (p>;0.05). In summary, our data suggest core temperature responses between participants in compensable conditions should be compared by administering exercise intensity based on heat production per unit mass, not absolute heat production or %VO 2peak . 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) | 0.001 | 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".