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Record W1975322966 · doi:10.1139/y02-109

Thermoregulation in the cold after physical training at different ambient air temperatures

2002· article· en· W1975322966 on OpenAlexvenueno aff
Jean‐Claude Launay, Yves Besnard, Angélique Guinet, Anne-Marie Hanniquet, Jacques Bittel, Gustave Savourey

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2002
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsnot available
Fundersnot available
KeywordsThermoregulationRectal temperatureAnimal scienceAcclimatizationSkin temperatureInterval trainingMedicineBiologyInternal medicineEcology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.032
GPT teacher head0.287
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2002
Admission routes1
Has abstractyes

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