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Record W1989047056 · doi:10.1260/0263-0923.30.4.291

Influence of Driving Speed, Terrain, Seat Performance and Ride Control on Predicted Health Risk Based on ISO 263I-I and EU Directive 2002/44/EC

2011· article· en· W1989047056 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.

Bibliographic record

VenueJournal of low frequency noise, vibration and active control · 2011
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsWestern UniversityLaurentian University
Fundersnot available
KeywordsTerrainDirectiveAccelerationWhole body vibrationAutomotive engineeringEngineeringSimulationVibrationComputer scienceAcousticsPhysicsGeography

Abstract

fetched live from OpenAlex

Operators of load-haul-dump (LHD) vehicles are commonly exposed to whole-body-vibration (WBV) levels above ISO 2631–1 and EU Directive 2002/44/EC guidelines. WBV was measured at the floor and seat while the same operator drove two LHDs on a controlled test track while driving speed, bucket load, ride control, terrain type, driving task, and seat optimization were varied. Frequency-weighted RMS acceleration was calculated and A(8) values were modeled for six driving scenarios. Vibration exposure was lowest when the LHD was driven at the lowest speed, forward, over smooth terrain, with ride control on and the bucket loaded (0.20 m/s 2 ). The A(8) decreased from 0.84 m/s 2 when driving with ride control off, over mixed terrain using all gears, to 0.53 m/s 2 when driving with ride control on and an optimized seat. The estimated daily exposure decreased but remained just above the ISO 2631–1 and EU Directive 2002/44/EC guidelines.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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