The Nature, Cause, and Extent of Occupational Musculoskeletal Injuries among Sonographers
Bibliographic record
Abstract
Concerns regarding injury rates, as well as resulting discomfort and disability, among sonographers led to a needs assessment across 13 work sites. General sonographers completed 82,642 exams in 2001-2002. Sick time and workers’ compensation costs of more than $180,000 occurred due to worker disability in the same time period. In an effort to improve working conditions and retain workers, funding was allocated to assess the problem and provide recommendations to prevent and manage the injuries more effectively. A survey was administered across the sector to 76 sonographers. The respondent rate was 88%. The results describe the nature of injury, types of scans causing discomfort, effectiveness of various treatments and providers, and workers’ feelings regarding work organization and culture. The results identify and validate the need for action. Recommendations include a standardized approach for treatment, education, and ergonomic work site training as well as prescreening of students for injury risk factors.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".