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Effect of water temperature on cooling efficiency during hyperthermia in humans

2003· article· en· W2126075331 on OpenAlexaff
Caroline Proulx, Michel B. Ducharme, Glen P. Kenny

Bibliographic record

VenueJournal of Applied Physiology · 2003
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsDefence Research and Development CanadaUniversity of Ottawa
Fundersnot available
KeywordsHyperthermiaThermoregulationEnvironmental scienceChemistryMaterials scienceMedicineInternal medicine

Abstract

fetched live from OpenAlex

We evaluated the cooling rate of hyperthermic subjects, as measured by rectal temperature (T(re)), during immersion in a range of water temperatures. On 4 separate days, seven subjects (4 men, 3 women) exercised at 65% maximal oxygen consumption at an ambient temperature of 39 degrees C until T(re) increased to 40 degrees C (45.4 +/- 4.1 min). After exercise, the subjects were immersed in a circulated water bath controlled at 2, 8, 14, or 20 degrees C until T(re) returned to 37.5 degrees C. No difference in cooling rate was observed between the immersions at 8, 14, and 20 degrees C despite the differences in the skin surface-to-water temperature gradient, possibly because of the presence of shivering at 8 and 14 degrees C. Compared with the other conditions, however, the rate of cooling (0.35 +/- 0.14 degrees C/min) was significantly greater during the 2 degrees C water immersion, in which shivering was seldom observed. This rate was almost twice as much as the other conditions (P < 0.05). Our results suggest that 2 degrees C water is the most effective immersion treatment for exercise-induced hyperthermia.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations249
Published2003
Admission routes1
Has abstractyes

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