O43-4 Evaluation of a hybrid expert approach for retrospective assessment of occupational exposures in a population-based study of prostate cancer in montreal, canada
Bibliographic record
Abstract
Objective To evaluate the performance of a hybrid expert approach for retrospective occupational exposure assessment. Methods PROtEuS is a population-based case-control study of prostate cancer in Montreal, Canada, comprising approximately 4000 subjects. Semi-structured interviews and questionnaires were used to collect lifetime occupational histories. Experts evaluated exposure to 345 agents, assigning semi-quantitative levels (3 categories) by certainty, intensity and frequency of exposure. Towards this, they used job-exposure profiles (JEPs) developed using traditional expert ratings from a case-control study of lung cancer conducted in Montreal in the 1990s. JEPs present summaries of ratings across agents by job title, as well as guidelines helping experts adjust their ratings based on specific exposure circumstances. We compared expert ratings with JEP distributions to evaluate how experts modulated their assessments beyond those proposed by the JEPs while taking into account the information provided by study subjects. We restricted comparisons to blue collar occupations, and to agents and 7-digit 1971 Canadian Classification and Dictionary of Occupation codes common between the two sets. Results A total of 279 agents and 667 blue collar occupations were retained for analysis. Experts rated exposures with higher certainty (OR 1.18, 95% CI: 1.16–1.21) and intensity (OR 1.07, 95% CI: 1.04–1.10) relative to JEPs, while the opposite trend was found for frequency (OR 0.75, 95% CI: 0.73–0.76). Weighted Kappa values for the agreement between the ratings assigned by experts with those with the highest proportion of jobs in JEPs was highest for frequency (0.70) and intensity (0.66) compared to certainty (0.44). Conclusions PROtEuS experts provided with JEPs rated exposures with higher certainty and intensity, and with lower frequency, compared to the ratings from the JEPs themselves. This suggests that experts can use subjects’ job descriptions to modulate the ratings proposed by JEPs towards an overall greater confidence in their occupational exposure assignments.
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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 | 0.056 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".