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Record W2140996534 · doi:10.1260/0263092001493047

Digit Skin Temperature Test for Peripheral Circulation Evaluation

2000· article· en· W2140996534 on OpenAlexaff
P. L. Pelmear, Dominique Ibañez, Gabrielle de Veber

Bibliographic record

VenueJournal of low frequency noise, vibration and active control · 2000
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsWellesley InstituteSt. Michael's Hospital
Fundersnot available
KeywordsVasospasmSkin temperatureAsymptomaticNumerical digitMedicineSurgeryAnesthesiaPhysical therapyDermatologyMathematics

Abstract

fetched live from OpenAlex

A test procedure for evaluating vasospasm in hand digits using cold water immersion at 15°C for a period of 10 minutes is described, and the result of initial and repeat tests on 25 subjects who volunteered for a control group study are reported. Digit skin temperatures were continuously recorded and the recovery temperatures were noted while the hands were immersed and for a further 10 minutes afterwards in air. Five from their history and test results were determined to have Raynaud's disease or Constitutional White Finger, and a further 5 subjects with no history of cold hands or Raynaud's phenomenon had non-repeatable test results indicative of an asymptomatic sub-clinical state. A statistical analysis of the results from the 15 normal control subjects provides reference data (means and standard deviations) for the maximum skin temperature at 10 minutes immersion, and the skin recovery temperatures post-cold stress at 1 minute intervals in air. This objective test is frequently used for evaluating cold induced vasospasm in hand digits, and the normative data provided will enable abnormal subjects to be identified. Additional reference data is provided for use with vibration exposed workers to permit the severity of the vasospasm to be graded in accordance with the Stockholm vascular scale for Hand-arm Vibration Syndrome (HAVS).

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.817
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.297
Teacher spread0.286 · 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

Citations1
Published2000
Admission routes1
Has abstractyes

Explore more

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