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Interconnections between thermal perception and exercise capacity in the heat

2010· review· en· W1590064986 on OpenAlexaff
Stephen S. Cheung

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2010
Typereview
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsBrock University
Fundersnot available
KeywordsPerceptionPsychologyThermal sensationMedicinePhysical medicine and rehabilitationNeuroscienceThermal comfort

Abstract

fetched live from OpenAlex

Some models of exercise regulation suggest that exercise performance, rather than being solely limited by the attainment of fatigue in one or more physiological systems, is modulated by psychological factors. Extrapolating from such models, exercise capacity and voluntary performance during exercise in hot environments may be governed by a complex interplay between the physiological effects of hyperthermia along with psychological input stemming from the conscious perception of the thermal environment. Evidence is emerging for a neuroanatomical basis for peripheral and central thermal receptors to elicit both a distinct physiological response such as shivering or sweating along with being mapped into an overall subjective sensation of homeostasis. Experimental evidence supporting this interactivity includes the demonstration that physiological manipulations, such as an increased fitness, appear to confer an attenuation of thermal discomfort during whole-body exercise despite similar levels of physiological strain. At the same time, psychological interventions have proven effective in decreasing perceived thermal strain and extending exercise performance in hot environments. The purpose of this review was to survey the potential interactions between thermal perception and exercise performance in the heat.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.119
GPT teacher head0.380
Teacher spread0.260 · 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 designOther design
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

Citations70
Published2010
Admission routes1
Has abstractyes

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