A comparison of thermoregulatory responses to exercise between mass-matched groups with large differences in body fat
Bibliographic record
Abstract
We sought to determine 1) the influence of adiposity on thermoregulatory responses independently of the confounding biophysical factors of body mass and metabolic heat production (Hprod); and 2) whether differences in adiposity should be accounted for by prescribing an exercise intensity eliciting a fixed Hprod per kilogram of lean body mass (LBM). Nine low (LO-BF) and nine high (HI-BF) body fat males matched in pairs for total body mass (TBM; LO-BF: 88.7 ± 8.4 kg, HI-BF: 90.1 ± 7.9 kg; P = 0.72), but with distinctly different percentage body fat (%BF; LO-BF: 10.8 ± 3.6%; HI-BF: 32.0 ± 5.6%; P < 0.001), cycled for 60 min at 28.1 ± 0.2 °C, 26 ± 8% relative humidity (RH), at a target Hprod of 1) 550 W (FHP trial) and 2) 7.5 W/kg LBM (LBM trial). Changes in rectal temperature (ΔTre) and local sweat rate (LSR) were measured continuously while whole body sweat loss (WBSL) and net heat loss (Hloss) were estimated over 60 min. In the FHP trial, ΔTre (LO-BF: 0.66 ± 0.21 °C, HI-BF: 0.87 ± 0.18 °C; P = 0.02) was greater in HI-BF, whereas mean LSR (LO-BF 0.52 ± 0.19, HI-BF 0.43 ± 0.15 mg·cm(-2)·min(-1); P = 0.19), WBSL (LO-BF 586 ± 82 ml, HI-BF 559 ± 75 ml; P = 0.47) and Hloss (LO-BF 1,867 ± 208 kJ, HI-BF 1,826 ± 224 kJ; P = 0.69) were all similar. In the LBM trial, ΔTre (LO-BF 0.82 ± 0.18 °C, HI-BF 0.54 ± 0.19 °C; P < 0.001), mean LSR (LO-BF 0.59 ± 0.20, HI-BF 0.38 ± 0.12 mg·cm(-2)·min(-1); P = 0.04), WBSL (LO-BF 580 ± 106 ml, HI-BF 381 ± 68 ml; P < 0.001), and Hloss (LO-BF 1,884 ± 277 kJ, HI-BF 1,341 ± 184 kJ; P < 0.001) were all greater at end-exercise in LO-BF. In conclusion, high %BF individuals demonstrate a greater ΔTre independently of differences in mass and Hprod, possibly due to a lower mean specific heat capacity or impaired sudomotor control. However, thermoregulatory responses of groups with different adiposity levels should not be compared using a fixed Hprod in watts per kilogram lean body mass.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".