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Record W2992884375

Review of legal suits involving hand-arm vibration

2011· article· en· W2992884375 on OpenAlexvenueno aff
Thomas Jetzer

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsnot available
Fundersnot available
KeywordsPlaintiffWork (physics)PopulationVibrationBusinessMedicineEngineeringForensic engineeringPhysical medicine and rehabilitationRisk analysis (engineering)PsychologyLawPolitical scienceEnvironmental healthMechanical engineeringAcoustics
DOInot available

Abstract

fetched live from OpenAlex

The characteristics of lawsuits involving hand-arm vibration (HAV), the medical issues involved, and the strategies of defense and plaintiff attorneys as noted in a particular occupational medicine practice, are outlined. The study finds that there is widespread lack of physician knowledge or appreciation for vibration-related upper extremity traumas. It is found that females doing jobs with high vibration exposure are noted to develop symptoms considerably faster and earlier then males. There must also be strong evidence that the vibration exposure has been long enough and sufficient to cause the pathology observed, taking into account the current standards. These legal suits may therefore have had a beneficial effect for the working population in general, as many companies are finally finding that it is more cost-effective to provide prevention and a proper work environment than to continue to fight or lose lawsuits.

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.881
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0150.017
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.041
GPT teacher head0.291
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2011
Admission routes1
Has abstractyes

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