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Record W2463590713 · doi:10.3233/oer-160239

Reducing whole-body vibration through field vibration tested heavy equipment seat retrofitting

2016· article· en· W2463590713 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOccupational Ergonomics · 2016
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsWestern UniversityLaurentian UniversityUniversity of Guelph
FundersWorkplace Safety and Insurance Board
KeywordsWhole body vibrationRetrofittingVibrationCushionTransmissibility (structural dynamics)Structural engineeringAutomotive engineeringEngineeringComputer scienceAcousticsVibration isolationPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Heavy mobile equipment operation exposes operators to whole-body vibration (WBV) through the seat. The decision of which seat to retrofit a machine with is usually done statically. OBJECTIVE: To report on the third phase of a three phase project designed to intelligently retrofit seats in heavy mobile machines with the purpose of reducing machine operator WBV exposure. METHODS: Three slag pot haulers were retrofitted with a 6801 Isringhausen seat in which the seat pan cushion was retrofitted with Skydex TM seating material. Vibration dose values (weighted for health), vibration total values (weighted for comfort) and Seat Effective Amplitude Transmissibility were determined from field measurements. RESULTS: WBV was reduced from the first field study to below the upper boundary of the ISO 2631-1 (1997) health guidance caution zone and comfort weighted vibration total values were reduced to the second lowest discomfort rating. CONCLUSIONS: Steel making and other similar industries have been provided with information to more efficiently retrofit existing machines.

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.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.032
GPT teacher head0.330
Teacher spread0.298 · 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