Whole body heat loss is reduced in older males during short bouts of intermittent exercise
Bibliographic record
Abstract
Studies in young adults show that a greater proportion of heat is gained shortly following the start of exercise and that temporal changes in whole body heat loss during intermittent exercise have a pronounced effect on body heat storage. The consequences of short-duration intermittent exercise on heat storage with aging are unclear. We compared evaporative heat loss (HE) and changes in body heat content (ΔHb) between young (20-30 yr), middle-aged (40-45 yr), and older males (60-70 yr) of similar body mass and surface area, during successive exercise (4 × 15 min) and recovery periods (4 × 15 min) at a fixed rate of heat production (400 W) and under fixed environmental conditions (35 °C/20% relative humidity). HE was lower in older males vs. young males during each exercise (Ex1: 283 ± 10 vs. 332 ± 11 kJ, Ex2: 334 ± 10 vs. 379 ± 5 kJ, Ex3: 347 ± 11 vs. 392 ± 5 kJ, and Ex4: 347 ± 10 vs. 387 ± 5 kJ, all P < 0.02), whereas HE in middle-aged males was intermediate to that measured in young and older adults (Ex1: 314 ± 13, Ex2: 355 ± 13, Ex3: 371 ± 13, and Ex4: 365 ± 8 kJ). HE was not significantly different between groups during the recovery periods. The net effect over 2 h was a greater ΔHb in older (267 ± 33 kJ; P = 0.016) and middle-aged adults (245 ± 16 kJ; P = 0.073) relative to younger counterparts (164 ± 20 kJ). As a result of a reduced capacity to dissipate heat during exercise, which was not compensated by a sufficiently greater rate of heat loss during recovery, both older and middle-aged males had a progressively greater rate of heat storage compared with young males over 2 h of intermittent exercise.
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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".