Comparisons of muscular activity in males and females while walking in restricted postures
Bibliographic record
Abstract
The purpose of this study was to examine differences in muscular activation between males and females while walking in restricted postures. Restricted postures are evident in various industries, including mining, construction and agriculture. These postures are associated with musculoskeletal disorders and lower back pain. Studies generally focus on a male workforce; however, more females are entering industrial workplaces. Twelve male and 12 female subjects between the ages of 18 and 25 years participated in the study. Subjects walked on a treadmill at a speed of 3.5 km/h for four minutes under conditions of upright walking, and stooped walking under restrictions at 85% and 70% of stature. Electromyographic activity was measured on seven muscles (trapezius, latissimus dorsi, erector spinae, rectus femoris, biceps femoris, medial gastrocnemius and tibialus anterior). Ratings of Perceived Exertion (RPE) and Body Discomfort were also obtained. The extent of vertical restriction significantly altered levels of muscle activation. Female subjects had significantly lower levels of activation of the medial gastrocnemius than males. Local RPE was greatest under the lowest restriction, and body discomfort of the neck, lower back and hamstrings was evident during restricted walking. Work place design and interventions should consider these consequences.
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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 | 0.001 |
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".