Predictive validity of a retrospective measure of noise exposure
Bibliographic record
Abstract
AIMS: To investigate the validity of measures of noise exposure derived retrospectively for a cohort of nuclear energy workers for the period 1950-98, by investigating their ability to predict hearing loss. METHODS: Subjects were men aged 45-65 chosen from a larger group of employees--assembled for a nested case-control study of noise and death from ischaemic heart disease--who had had at least one audiogram after at least five years' work. Average hearing loss, across both ears and the frequencies 0.5, 1, 2, and 4 kHz, was calculated from the last audiogram for each man. Previous noise exposure at work was assessed retrospectively by three hygienists using work histories, noise survey records from 1965-98, and judgement about use of hearing protection devices. Smoking and age at the time of the audiogram were extracted from records. Differences in hearing loss between men categorised by cumulative noise exposure were assessed after controlling for age, smoking, year of test, and previous test experience. RESULTS: There were 186 and 150 eligible subjects at sites A and B of the company respectively who were employed for an average of 20 years. Compared to men with less than one year's exposure to levels of 85dB(A) or greater, hearing loss was greater by 3.7 dB (90% CI -2.6 to 10.1), 3.8 dB (90% CI -2.6 to 10.3), 7.0 dB (90% CI 1.1 to 12.9) and 10.1 dB (90% CI 4.2 to 16.0) in the lowest to highest categories of cumulative noise exposure at site B. In contrast, at site A, the corresponding figures were -2.2 dB, -2.4 dB, -1.8 dB, and -4.4 dB, with no confidence interval excluding zero. CONCLUSIONS: Noise estimation at one site was shown to have predictive validity in terms of hearing loss, but not at the other site. Reasons for the differences between sites are discussed.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".