Evaluating risks for the upper extremity during the installation of electrical meters
Bibliographic record
Abstract
Installation of electrical meters is an occupational task that may place utility employees at risk of upper extremity discomfort or disorders. This study focused on identifying the most preferable installation technique from several alternatives using a combination of professional utility employees and experimental subjects. Factors considered included variation in installation height, the use of a hand-held mallet, lubrication applied to the meter and the use of one vs. two hands for installation. Installing meters located above shoulder height resulted in a two-fold increase in both peak and cumulative hand acceleration and pressure. Further, the use of a force-absorbing striking mallet showed significantly lowered peak pressure (60%) compared to other techniques. Peak acceleration and cumulative pressure were significantly lower than other techniques for both experienced and inexperienced subjects when using the mallet. Additionally, the mallet installations had amongst the lowest ratings of perceived exertion across installation types. Thus, the primary recommendations for meter installation with respect to the analyzed scenarios are to use a force-absorbing striking mallet and avoid installations at high locations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".