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Record W1984611386 · doi:10.1007/s00421-011-2233-4

Trainability of cold induced vasodilatation in fingers and toes

2011· article· en· W1984611386 on OpenAlexaff
H.A.M. Daanen, Jens Koedam, Stephen S. Cheung

Bibliographic record

VenueEuropean Journal of Applied Physiology · 2011
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsBrock University
Fundersnot available
KeywordsMedicineSkin temperatureFoot (prosody)Cold sensitivityAnesthesiaVasodilationForearmPeripheralSurgeryPhysical therapyInternal medicineChemistryDermatology

Abstract

fetched live from OpenAlex

Subjects that repeatedly have to expose the extremities to cold may benefit from a high peripheral temperature to maintain dexterity and tissue integrity. Therefore, we investigated if repeated immersions of a hand and a foot in cold water resulted in increased skin temperatures. Nine male and seven female subjects (mean 20.4; SD 2.2 years) immersed their right (trained) hand and foot simultaneously in 8°C water, 30 min daily for 15 days. During the pre and post-test (days 1 and 15, respectively) the left (untrained) hand and foot were immersed as well. Pain, tactile sensitivity and skin temperatures were measured every day. Mean (SD) toe temperature of the trained foot increased from 9.49°C (0.89) to 10.03°C (1.38) (p < 0.05). The trained hand, however, showed a drop in mean finger temperature from 9.28°C (0.54) to 8.91°C (0.44) (p < 0.001) and the number of cold induced vasodilation (CIVD) reactions decreased from 52% during the first test to 24% during the last test. No significant differences occurred in the untrained extremities. Pain diminished over time and tactile sensitivity decreased with skin temperature. The combination of less CIVD responses in the fingers after training, reduced finger skin temperatures in subjects that did show CIVD and the reduced pain and tactile sensitivity over time may lead to an increased risk for finger cold injuries. It is concluded that repeated cold exposure of the fingers does not lead to favorable adaptations, but may instead increase the injury risk.

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 score0.961
Threshold uncertainty score0.200

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 head0.058
GPT teacher head0.262
Teacher spread0.204 · 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

Citations42
Published2011
Admission routes1
Has abstractyes

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