Comparison of ergonomic risk assessment output in a repetitive sawmill occupation: Trim-saw operator
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multiple ergonomic risk assessment methods of unique structure are currently being used to direct industrial prevention initiatives focused on musculoskeletal injuries. In this study, the physical exposures required to perform an at-risk sawmill occupation were collected from 29 subjects via quantified means (surface electromyography and electrogoniometery) and used to calculate several ergonomic risk assessment methods. The aims of this study are to: 1) compare the output of the RULA, REBA, ACGIH TLV, Strain Index and OCRA ergonomic risk assessment methods, 2) examine the assessments' ability to differentiate between facilities reporting meaningfully different incidence rates, and 3) examine the effect of varying the definition of end range posture and exertion required on risk assessment scores. Risk level output assigned by all methods were not sensitive to inter facility differences in risk of injury, suggesting interpretation of risk index and component scores are needed to direct intervention. Components of all methodologies were sensitive to worker technique and facility assessed. Varying variable definition resulted in significantly different component, combined component and/or risk output scores in all methods assessed. The significant effect of posture and exertion variable definition suggests definitions taken to be interchangeable by work site evaluators are not equivalent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 it