Hand-Arm Vibration of Unskilled Oil Palm Motorised Cutter Operator
Bibliographic record
Abstract
The portable petrol driven oil palm motorised cutter or CANTAS has been identified as a type of machine that generates hand-arm vibration. These vibrations can cause complex vascular, neurological and musculoskeletal disorder known as hand-arm vibration syndrome (HAVS) when over exposure of daily usage. The objective of this study is to investigate the vibration level at different angles during the operational of the CANTAS including idle and full throttle conditions. The CANTAS vibration experiments were carried out at a farm in Parit Raja, Batu Pahat, Johor. A student participated as the unskilled worker and was assisted by two technical staffs to conduct the vibration measurements. The measurement was taken during the operations of cutting first fronds, second fronds and a fruit bunch during idle and full throttle conditions and by varying the inclination angle. The inclinations of cutting angle were varied from 45º, 60º and 75º. The hand-arm vibration value, ahv achieved 10.93 ±1.2 m/s2 and 7.94 ± 1.0 m/s2 for unskilled user during operation of two bunches and one pruning frond for all angles at point 1 and point 2 handle respectively. Mean vibration values at both point of handles resulted in vibration values of 10.12±3.8m/s2 at 450, 9.15±3.0m/s2 at 600 and 9.03±1.8m/s2 at 750. Increasing the angle overall results in decreasing the level of vibration at both handle points.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".