O-89 Using proxy respondents when assessing occupational circumstances: impact on expert assessments of reliability in the assignment of chemical exposures
Bibliographic record
Abstract
Introduction Exposure misclassification can occur when information on occupational circumstances is derived from interviews conducted with proxy respondents. It is unknown whether this can impact reliability ratings (confidence that the exposure actually occurred) by experts who assign chemical exposures based on job descriptions. We aimed to assess differences in reliability level assignments when information is derived from interviews conducted with proxy respondents versus self-respondents. Material and Methods Data were collected in the context of the Prostate cancer & Environment Study (PROtEuS), which included 1,937 prostate cancer cases and 1,994 population controls. Complete occupational histories were collected during in-person interviews with proxies (n=135) and self-respondents (n=3,790). Industrial hygienists conducted semi-quantitative evaluations of exposure, including reliability, to about 300 agents. Results In total, 129,297 and 4,275 chemical exposures were derived from interviews from self and proxy respondents, respectively. Most assignments were from blue-collar jobs (77%). Based on the latter, experts most often assigned exposures with a low reliability level when information was provided by proxies (23% vs 12% of exposures), without any notable difference when considering the case or control status. Similar results were found in analyses focusing on exposures in common occupations such as firefighters (low reliability; proxies: 48% vs self-respondents: 12%). For motor-vehicle mechanics and repairmen, most exposures were assigned with a medium or high reliability, the latter being slightly more frequent among self-respondents (72% vs 60%). Some inverse findings emerged for exposures among truck drivers, particularly among controls (low reliability; proxies: 5% vs self-respondents: 16%). Conclusion Reliability ratings by experts assigning chemical exposures were generally lower when information on occupational circumstances was derived from interviews conducted with proxy respondents, irrespective of case/control status, but exceptions occurred for certain occupations.
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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 | 0.140 | 0.262 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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 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".