Fitness‐related differences in the rate of whole‐body total heat loss in exercising young healthy women are heat‐load dependent
Bibliographic record
Abstract
New Findings What is the central question of this study? Aerobic fitness modulates heat loss, albeit the heat load at which fitness‐related differences occur in young healthy women remains unclear. What is the main finding and its importance? We demonstrate using direct calorimetry that fitness modulates heat loss in a heat‐load dependent manner, with differences occurring between young women of low and high fitness and matched physical characteristics when the metabolic heat load is at least 400 W in hot, dry conditions. Although fitness has been known for some time to modulate heat loss, our findings define the metabolic heat load at which fitness‐related differences occur. Abstract Aerobic fitness has recently been shown to alter heat loss capacity in a heat‐load dependent manner in young men. However, given that sex‐related differences in heat loss capacity exist, it is unclear whether this response is consistent in women. We therefore assessed whole‐body total heat loss in young (21 ± 3 years old) healthy women matched for physical characteristics, but with low (low‐fit; 35.8 ± 4.5 ml O2 kg−1 min−1) or high aerobic fitness (high‐fit; 53.1 ± 5.1 ml O2 kg−1 min−1; both n = 8; indexed by peak oxygen consumption), during three 30 min bouts of cycling performed at increasing rates of metabolic heat production of 250 (Ex1), 325 (Ex2) and 400 W (Ex3), each separated by a 15 min recovery, in hot, dry conditions (40°C, 11% relative humidity). Whole‐body total heat loss (evaporative ± dry heat exchange) and metabolic heat production were measured using direct and indirect calorimetry, respectively. Body heat content was measured as the temporal summation of heat production and loss. Total heat loss did not differ during Ex1 (low‐fit, 215 ± 16 W; high‐fit, 231 ± 20 W; P > 0.05) and Ex2 (low‐fit, 278 ± 15 W; high‐fit, 301 ± 20 W; P > 0.05), but was lower in the low‐fit (316 ± 21 W) compared with the high‐fit women (359 ± 32 W) during Ex3 (P < 0.01). Consequently, the low‐fit group stored 1.3‐fold more heat (429 ± 61 kJ) throughout the three exercise bouts relative to the high‐fit group (330 ± 113 kJ; P < 0.05). We show that aerobic fitness independently modulates heat loss capacity during exercise in hot, dry conditions in women separated by a peak oxygen consumption of ∼17 ml O2 kg−1 min−1 starting at a metabolic heat load of 400 W.
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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".