Quantifying the Trunk and Humeral Postural Demands of Uranium Mine Site Workers Using Wearable Sensors
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to quantify and describe humeral and trunk ergonomic exposures across various occupations on a mine site. METHODS: Thirteen mine site workers from eleven different occupations were outfitted with wearable sensors to measure trunk and humeral kinematics during one to four natural on-site work tasks. Trunk flexion/extension and humeral elevation 10th, 50th, 90th and 99th percentiles, range, percent time in neutral and extreme posture, rate of movement repetition, mean angular velocity, and percent time working at slow and fast speed were calculated for each work task. RESULTS: Various degrees of ergonomic exposure were measured in the different occupations and work tasks; however, the housekeeping work was consistently the highest exposure task across many of the outcomes. CONCLUSIONS: Future work should examine strategies for reducing the physical demand in work tasks identified as high exposure.
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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 | 0.001 | 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) | 0.001 | 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; 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".