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Record W2991975327

New standard criteria for cold provocation test with hand immersion for cases of HAVS in Japan

2011· article· en· W2991975327 on OpenAlexvenueno aff
Tatsuya Ishitake, Shuji Sato, Yukinori Kume, Tsutomu Nagase, Hisataka Sakakibara, Norikuni Toibana, Youichi Kurozawa, Kazuhisa Miyashita, Hossein Mahbub, Noriaki Harada

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsProvocation testHammerSensitivity (control systems)MedicineStructural engineeringEngineeringPathology
DOInot available

Abstract

fetched live from OpenAlex

A national standard for cold-water provocation tests based on an analysis of Japanese multi-institutional data was established. Data was collected from 872 individuals who underwent cold-water provocation testing at 7 institutions. Three indices were used for the analysis of finger skin temperature and the scores from the 3 indices were incorporated into an evaluation system that logically combined them. The results show that the most frequently used vibrating tools were chain saws (34%) and chipping hammer (25%) in the patient group. When compared to the control group, members of the patient group with vibration white finger (VWF) had significantly lower average values for the 3 indices. The sensitivity and specificity of the scored method are found to be 7 1.7% and 72.0%, while the logical combination evaluation system yielded sensitivity and specificity values of 70.6% and 74.0%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.038
GPT teacher head0.290
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

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
Published2011
Admission routes1
Has abstractyes

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