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Record W2155919786 · doi:10.1093/annhyg/mep035

Comparing Three Methods for Evaluating Impact Wrench Vibration Emissions

2009· article· en· W2155919786 on OpenAlexaff
Thomas W. McDowell, Daniel E. Welcome, Ren G. Dong

Bibliographic record

VenueThe Annals of Occupational Hygiene · 2009
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsWrenchVibrationBrakeAutomotive engineeringEngineeringComputer scienceStructural engineeringReliability engineering

Abstract

fetched live from OpenAlex

To provide a means for comparing impact wrenches and similar tools, the international standard ISO 8662-7 prescribes a method for measuring the vibrations at the handles of tools during their operations against a cotton-phenolic braking device. To improve the standard, alternative loading mechanisms have been proposed; one device comprises aluminum blocks with friction brake linings, while another features plate-mounted bolts to provide the tool load. The objective of this study was to evaluate these three loading methods so that tool evaluators can select appropriate loading devices in order to obtain results that can be applied to their specific workplace operations. Six experienced tool operators used five tool models to evaluate the loading mechanisms. The results of this study indicate that different loads can yield different tool comparison results. However, any of the three devices appears to be adequate for initial tool screenings. On the other hand, vibration emissions measured in the laboratory are unlikely to be fully representative of those in the workplace. Therefore, for final tool selections and for reliably assessing workplace vibration exposures, vibration measurements should be collected under actual working conditions. Evaluators need to use appropriate numbers of tools and tool operators in their assessments; recommendations are provided.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.643
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.383
GPT teacher head0.585
Teacher spread0.202 · 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

Citations15
Published2009
Admission routes1
Has abstractyes

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