Evaluation of Effect of Handle Vibration Diesel-Fueled Single-Axle Tractor on Handgrip Strength of Operators
Bibliographic record
Abstract
Abstract Background : The transmission of vibration from a single-axis tractor to the human body is determined by its dynamic response; this, in turn, depends on the physical characteristics of a person's hand, the contact area, the strength of the grip, the push force of the tractor, and the position. The purpose of this work was to measure and evaluate handgrip strength and fatigue resistance for operators of a 15 horsepower single-axle tractor before and after vibration exposure. Methods : Grip strength of dominant and non-dominant hands before and after 30 minutes of tilling operations was measured and recorded. The operators performed tilling tasks with the tractor in third gear, while the vibration levels were measured at the tractor handle along with the vertical, forward, and transverse directions. Results : The average operator grip strength was 33.6 ± 2.7 and 26.3 ± 3.3 kg and the average overall grip strength declined from 39.7 to 29.31 kg, although the average fatigue strength was 27.6 and 26.5 seconds for the dominant hand before and after vibration exposure. For the non-dominant hand, the mean grip strength measured was 28.7±2.9 and 23.1±1.9 kg and the maximum grip strength was 32.79 and 26.25, while fatigue was 29.76 and 22 seconds before and after tilling respectively. Conclusion : The average reduction in grip strength suggest considerable differences in grip strength for dominant and non-dominant hands of single axle tractor operators and shows that vibration transmitted from the single axle tractor handle has a major effect on the operators.
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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 | 0.047 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".