Development of a Systematic Observation Protocol of Physical Exposure of the Back: A Preliminary Study
Bibliographic record
Abstract
OBJECTIVE: At present there is no systematic observation protocol for the assessment of the multi-factorial aspects of physical exposure related to the back used within the constraints of occupational epidemiological research. In this context, a new preliminary systematic observation protocol is proposed to assess exposure to physical loading of the back using nine categories of physical risk factors: the SOPE back protocol. The objective of this study was to investigate whether the new protocol can correctly identify the level of exposure related to measured physical loading of the back. METHODS: The subjects of this closed cohort study were 451 manual workers at a natural gas distribution company. The assessment of exposure was made with the protocol using groups with different job titles. The workers were followed for a 2 yr period to establish the risk of a new occurrence of complete disability related to the back (NOCD back injury) in each job grouping. RESULTS: Based on the median of the total scores derived from the protocol, two levels of exposure were identified (high and low). CONCLUSION: Taking into account the limitations of this study, the protocol in development may be a good tool to establish two levels of exposure to physical loading of the back in large epidemiological studies of occupational low back pain. Further research is needed to replicate these results with larger samples and to test the reliability and predictive validity of the protocol.
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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 | 0.157 | 0.158 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".