Evaluation of Low Back Pain Risks in a Beef Skinning Operation
Bibliographic record
Abstract
The low back pain risks in a beef skinning operation at a high stand kill floor workstation was evaluated. The increases in compressive forces at lower back (L5/S1) between normal slump (back angle 25 degrees, measured in the sagittal plane) and severe (45 degrees ) and between normal slump and very severe (70 degrees ) bent back postures were 387 N or 28% and 616 N or 45%, respectively. The high spine load coupled with high level of repetition can have a high probability of fatigue failure in the spine structural members. Non-neutral back posture for a large portion of the total work time can be a low back pain risk factor. The videotape analysis showed that the times involved during the task performance for the bent back (more than 25 degrees ) and severe bent back (more than 45 degrees ) were 48.4 and 33.5% of the total cycle time, respectively. The upper limit from OWAS (Ovako Working Posture Analysis System) for bent back posture is 30% of the total cycle time. The bent and twisted back posture (both more than 25 degrees ) time was 10.4% compared to OWAS limit of 5%. This indicated that actions are needed in the near future to alleviate the risk of low back pain. Ergonomics redesign of the workstation was recommended for the operation.
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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 | 0.001 | 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".