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Record W4389967016 · doi:10.14814/phy2.15893

Effects of skin and mild core cooling on cognitive function in cold air in men

2023· article· en· W4389967016 on OpenAlexafffund
Phillip J. Wallace, Dominique D. Gagnon, Geoffrey L. Hartley, Michael J. Taber, Stephen S. Cheung

Bibliographic record

VenuePhysiological Reports · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsCanadian Sleep SocietyNipissing UniversityLaurentian UniversityBrock University
FundersDalhousie UniversityNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsWorking memoryChoice reaction timeCognitionCore (optical fiber)Skin temperatureTask (project management)AudiologyMedicineChemistryBiomedical engineeringComputer scienceTelecommunicationsPsychiatryEngineering

Abstract

fetched live from OpenAlex

This study tested the effects of skin and core cooling on cognitive function in 0°C cold air. Ten males completed a randomized, repeated measures study consisting of four environmental conditions: (i) 30 min of exposure to 22°C thermoneutral air (TN), (ii) 15 min to 0°C cold air which cooled skin temperature to ~27°C (CS), (iii) 0°C cold air exposure causing mild core cooling of ∆-0.3°C from baseline (C-0.3°C) and (iv) 0°C cold air exposure causing mild core cooling of ∆-0.8°C from baseline (C-0.8°C). Cognitive function (reaction time [ms] and errors made [#]) were tested using a simple reaction test, a two-six item working memory capacity task, and vertical flanker task to assess executive function. There were no condition effects (all p > 0.05) for number of errors made on any task. There were no significant differences in reaction time relative to TN for the vertical flanker and item working memory capacity task. However, simple reaction time was slower in C-0.3°C (297 ± 33 ms) and C-0.8°C (296 ± 41 ms) compared to CS (267 ± 26 ms) but not TN (274 ± 38). Despite small changes in simple reaction time (~30 ms), executive function and working memory was maintained in 0°C cold air with up to ∆-0.8°C reduction in core temperature.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.240

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)0.0000.000

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 head0.074
GPT teacher head0.327
Teacher spread0.253 · 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.

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

Citations5
Published2023
Admission routes2
Has abstractyes

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