Biomechanical shoulder loads and postures in light automotive assembly workers: Comparison between shoulder pain/no pain groups
Bibliographic record
Abstract
BACKGROUND: The number of workplace shoulder compensation claims resulting from musculoskeletal disorders (MSDs) has decreased slightly in recent years, however the median number of days off work remains unchanged, which suggests an increase in injury severity. Little information is available regarding cumulative shoulder exposures, and there is no information on their impact on shoulder pain. METHODS: Seventy-nine automotive seat frame assembly workers completed a questionnaire about the prevalence and severity of shoulder pain and were videotaped performing assembly tasks. 3DMatch, a posture-matching software program, was used to calculate the peak and cumulative shoulder moments and forces by matching postures seen in the video with predetermined ranges of posture to be used in the biomechanical model. RESULTS: Of the 45.6% who reported shoulder pain, there was a mild correlation of pain severity with posterior shear of the shoulder. There were no significant differences in peak loads between Pain and No Pain groups; however, the No Pain group experienced significantly more cumulative caudal shear. CONCLUSION: Although there was no difference in percent time spent in different flexed postures between pain groups, those working some jobs may be at an increased risk of developing MSDs based on the amount of time spent in flexed postures, as well as the peak flexion moment acting on the shoulder.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".