MétaCan
Menu
Back to cohort
Record W2011660233 · doi:10.1260/0263-0923.30.3.197

Examination of Vibration Characteristics, and Reported Musculoskeletal Discomfort for Workers Exposed to Vibration via the Feet

2011· article· en· W2011660233 on OpenAlexafffund
Mallorie Leduc, Tammy Eger, Alison Godwin, James P. Dickey, Ron House

Bibliographic record

VenueJournal of low frequency noise, vibration and active control · 2011
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsSt. Michael's HospitalWestern UniversityUniversity of TorontoLaurentian University
FundersWorkplace Safety and Insurance Board
KeywordsVibrationWhole body vibrationAccelerometerFoot (prosody)MedicinePhysical medicine and rehabilitationPhysical therapyAcousticsComputer sciencePhysics

Abstract

fetched live from OpenAlex

The frequency and amplitude characteristics of vibration experienced at the feet under typical mining equipment operation were documented in this study. Foot-transmitted vibration (FTV) was measured using a tri-axial accelerometer mounted at the location where the worker stood. A musculoskeletal disorder questionnaire, work history and demographic information were also collected. Vibration from locomotives (primary source exposure) had a dominant frequency below 6.3 Hz; whereas, drilling and raise platforms (secondary source exposures) were predominantly in the 31.5 to 40 Hz range. All workers reported lower limb discomfort and two had been diagnosed with vibration induced white feet. All raise platforms exposed the workers to vibration levels that placed them above the ISO 2631–1 health guidance caution zone for an 8-hour exposure. Further investigation using both ISO 2631–1 and ISO 5341–1 standards is needed to determine long-term health effects to the whole-body and feet of workers exposed to FTV.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.287
Teacher spread0.264 · 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
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

Citations17
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueJournal of low frequency noise, vibration and active controlSame topicEffects of Vibration on HealthFrench-language works237,207