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 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 | 0.111 | 0.204 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".