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Local cold acclimation of the hand impairs thermal responses of the finger without improving hand neuromuscular function

2005· article· en· W2092151788 on OpenAlexaff
Carla Geurts, Gordon G. Sleivert, Stephen S. Cheung

Bibliographic record

VenueActa Physiologica Scandinavica · 2005
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsDalhousie UniversityCanadian Sport Centre PacificUniversity of New Brunswick
Fundersnot available
KeywordsAcclimatizationMedicineContraction (grammar)AnatomyAnesthesiaAnimal scienceChemistryInternal medicineBiologyBotany

Abstract

fetched live from OpenAlex

AIM: To investigate the effects of cold acclimation on the thermal response and neuromuscular function of the hand. METHODS: Ten healthy subjects [three female, seven male, age (mean +/- SD): 27.9 +/- 7.9 years] immersed their right hand in 8 degrees C water for 30 min, 5 days a week for 3 weeks. On the first and the last day, neuromuscular function of the first dorsal interosseus (FDI) muscle was tested. RESULTS: There was no significant change in maximal voluntary contraction strength or evoked contractile characteristics of the FDI after cold acclimation. Minimum finger temperature decreased significantly from 10.6 +/- 1.2 to 9.3 +/- 0.8 degrees C after 3 weeks (P < 0.01), with most of the decrease occurring after a single exposure. Mean finger temperature dropped significantly from 14.2 +/- 1.9 to 11.7 +/- 1.4 degrees C following cold acclimation (P < 0.05), with 90% of this adaptation occurring after 5 days. Onset time of cold-induced vasodilatation increased from 446 +/- 171 to 736 +/- 384 s (P < 0.05) and the amplitude decreased from 5.3 +/- 3.2 to 2.5 +/- 2.1 degrees C (P < 0.05). This was significantly different from the control group, who immersed their right hand on the first and last days only. CONCLUSION: These data suggest that cold acclimation does not enhance hand temperature or function but may put the hands at a greater risk of cold injury when exposed to the cold.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.364

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 studies0.0000.001
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 head0.019
GPT teacher head0.262
Teacher spread0.242 · 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 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

Citations31
Published2005
Admission routes1
Has abstractyes

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