Occupational disability related to back pain: Application of a theoretical model of work disability using prospective cohorts of manual workers
Bibliographic record
Abstract
BACKGROUND: A new model of work disability was developed based on the assumption that four different groups of workers are present at the beginning of a prospective epidemiologic study: one group of workers without back pain, and three groups of workers with back pain and a gradient of work disability. The goal of this research was to verify if these groups comprise workers at different levels of risk of occurrence of complete work disability related to back injury. METHODS: Prospective cohorts of manual workers (n=578) were followed for 1 year to document the risk of occurrence of complete disability related to back injury. RESULTS: The results showed that the workers who presented with back pain without work disability at the beginning of the study were at less risk compared to all the other workers in the cohort. Moreover, an effect modification was found between the workers who initially presented with back pain without work disability and a past history of compensation for back injury, adding credence to the non-similarity of these workers to the others. CONCLUSIONS: Based on these results, further studies should focus on improving the knowledge of the characteristics of these workers leading to a better understanding of how to prevent occupational low-back pain.
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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 | 0.024 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".