Validation of expert assessment of occupational exposures
Bibliographic record
Abstract
BACKGROUND: Assessment by experts may be the best method available for retrospective occupational exposure measurement in community-based studies. This study was undertaken to examine the validity of occupational exposure assessment by comparing the ratings of experienced raters with previously recorded industrial hygiene measurements. METHODS: We obtained 50 measurements from industrial hygiene records, covering a variety of jobs and substances and created 47 job descriptions around these measurements. Three raters were asked to assess exposure to a checklist of 19 substances (including those substances which had been measured). We estimated the sensitivity of the raters in correctly detecting those substances known to have been present. RESULTS: Using a liberal criterion for the ratings, the average sensitivity among the raters was 90%. Using a more stringent criterion, the average sensitivity was 73%. Among substances coded as present, the raters were quite accurate in rating the relative concentration and frequency of exposure. CONCLUSIONS: This trial demonstrated that a team of experienced raters could successfully characterize jobs in which important exposures occurred.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".