Surveillance of hearing loss among older construction and trade workers at Department of Energy nuclear sites
Bibliographic record
Abstract
BACKGROUND: Medical screening programs at three Departments of Energy (DOE) nuclear weapons facilities (Hanford Nuclear Reservation, Oak Ridge, and the Savannah River Site) have included audiometric testing since approximately 1996. This report summarizes hearing evaluations through March 31, 2003. METHODS: Occupational examinations included a medical history, limited physical examination, and tests for medical effects from specific hazards, including audiometric testing. Hearing thresholds by frequency for DOE workers were compared to age-standardized thresholds among an external comparison population of industrial workers with noise exposures <80 dBA. Multivariate analyses were used to explore the risk of hearing impairment by duration of construction trade work and self-reported noise exposure, while controlling for potential confounders such as age, race, sex, smoking, elevated serum cholesterol, hypertension, solvent exposures, and recreational noise exposures. RESULTS: Hearing thresholds among DOE workers were much higher than observed in a comparison population of industrial workers with low noise exposures. Overall, 59.7% of workers examined were found to have material hearing impairment by NIOSH criteria. Age, duration of construction work, smoking, and self-reported noise exposure increased the risk of hearing loss. The risk of material hearing impairment was significantly elevated for construction trade workers compared to the external comparison population (odds-ratio = 1.6, 95% CI = 1.3-2.1) and increased with the duration of trade work. CONCLUSIONS: These medical screening programs confirm worker concerns about risks for hearing loss and the need for hearing conservation programs for construction workers, with emphasis on the prevention of noise exposures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".