Exposure to whole-body vibration and seat transmissibility in a large sample of earth scrapers
Bibliographic record
Abstract
BACKGROUND: It is often difficult to access a large sample of vehicles in various work environments to evaluate worker exposure to vibration such as in construction and mining. Thus the main purpose of the present research was to test vibration exposure in a relatively large number of earth scrapers. The second aim was to assess vibration exposure values on seat transmissibility. STUDY DESIGN: 33earth scrapers were assessed for both exposure to whole-body vibration and seat transmissibility. METHOD: Two triaxial accelerometers, one placed on the seat and one on the floor directly below the seat, were used to gather whole-body vibration values (a(w)). Each machine was tested for a minimum of three complete work cycles: idling, scraping, travelling full, dumping, travelling empty back to the scrape site. RESULTS: Results showed that idling and scraping produced low levels of vibration when compared to travelling and dumping. Second, when the a(w) values were compared to the EU safety standards for an eight hour work day, the data (z axis) exceeded the exposure action value (0.5 m/s2) in all machines, and the exposure limit value (1.15 m/s2) in some. Implications; Operators of the scrapers were being exposed to unsafe levels of whole-body vibration. When the seats were assessed to see whether they were attenuating operator exposure to vibration, many of the seat effective amplitude transmissibility (SEAT) values exceeded 1.0. This meant that some of the seats were actually amplifying the vibration present at the floor, particularly in the y axis. CONCLUSION: Travelways should be kept smooth, operating speeds reduced, and new seats, effective in all three axes, designed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".