Influence of aerobic fitness and body fatness on tolerance to uncompensable heat stress
Bibliographic record
Abstract
This study examined the independent and combined importance of aerobic fitness and body fatness on physiological tolerance and exercise time during weight-bearing exercise while wearing a semipermeable protective ensemble. Twenty-four men and women were matched for aerobic fitness and body fatness in one of four groups (4 men and 2 women in each group). Aerobic fitness was expressed per kilogram of lean body mass (LBM) to eliminate the influence of body fatness on the expression of fitness. Subjects were defined as trained (T; regularly active with a peak aerobic power of 65 ml x kg LBM(-1) x min(-1)) or untrained (UT; sedentary with a peak aerobic power of 53 ml x kg LBM(-1) x min(-1)) with high (High; 20%) or low (Low; 11%) body fatness. Subjects exercised until exhaustion or until rectal temperature reached 39.5 degrees C or heart rate reached 95% of maximum. Exercise times were significantly greater in T(Low) (116 +/- 6.5 min) compared with their matched sedentary (UT(Low); 70 +/- 3.6 min) or fatness (T(High); 82 +/- 3.9 min) counterparts, indicating an advantage for both a high aerobic fitness and low body fatness. However, similar effects were not evident between T(High) and UT(High) (74 +/- 4.1 min) or between the UT groups (UT(Low) and UT(High)). The major advantage attributed to a higher aerobic fitness was the ability to tolerate a higher core temperature at exhaustion (the difference being as great as 0.9 degrees C), whereas both body fatness and rate of heat storage affected the exercise time as independent factors.
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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) | 0.001 | 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".