Thermoregulation in the cold after physical training at different ambient air temperatures
Bibliographic record
Abstract
Since human thermoregulation at rest is altered by cold exposure, it was hypothesized that physical training under cold conditions would alter thermoregulation. Three groups (n = 8) of male subjects (mean age 24.3 +/- 0.9 years) were evaluated: group T (interval training at 21 degrees C), group CT (interval training at 1 degrees C), and group C (no training, equivalent exposure to 1 degrees C). Each group was submitted, before and after 4 weeks of interval training (5 d/week), to a cold air test at rest (SCAT) (dry bulb temperature (Tdb) = 1 degrees C) for a 2-h period for evaluation of the thermoregulatory responses. During SCAT, after the training/acclimation period, group T exhibited a higher rectal temperature (Tre) (P < 0.05) without significant change in mean skin temperature (Tsk) whereas metabolic heat production (M) was higher at the beginning of the SCAT (P < 0.05). For group CT, no thermoregulatory change was observed. Group C showed a lower Tre (P < 0.05) without significant change in either Tsk or in M, suggesting the development of a hypothermic general cold adaptation. This study showed, first, that the cold thermoregulatory responses induced by an interval training differed following the climatic conditions of the training and, second, that this training performed in the cold prevented the development of a general cold adaptation.
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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".