S10-3 Establishing national carcinogen exposure (CAREX) programs in latin america and the caribbean: achievements and future directions
Bibliographic record
Abstract
Objective Cancer is the second-leading cause of death in Latin America and the Caribbean (LAC). Exposure to workplace carcinogens is an important factor, yet there are sparse data about the numbers and types of LAC workers exposed. This project aimed to build capacity for CARcinogen EXposure (CAREX) programs in LAC. Methods The CAREX method, originally developed in the European Union for estimating exposure to occupational carcinogens, has been used and modified in some Central American countries and Canada. Generally, the approach combines labour force data with estimates of the proportions of workers exposed to priority carcinogens in each country. A two-day workshop involving over 20 participants from Canada and 12 LAC countries was held to discuss methodological approaches, issues unique to LAC, and research opportunities. Certain individual countries subsequently developed CAREX programs by holding consultations to identify priority carcinogens and adapting proportion of exposure values from existing CAREX programs. Results CAREX programs in LAC have been established in Costa Rica, Nicaragua, Panama, Guyana, Colombia, Peru, and Chile. Central American CAREX projects included exposure estimates by sex for approximately 30–35 carcinogens that incorporated levels of uncertainty. Both informal and formal workers were covered in exposure estimates, although estimates for these populations are challenging in most countries. In general, agents with the greatest prevalence of exposure in all industries included solar radiation, environmental tobacco smoke, crystalline silica, and pesticides. In Peru, exposure estimates were based on data from LAC and Europe with the involvement of experts from 43 institutions. Preliminary results from Chile have also been produced using a slight variation of this approach. Conclusions This project demonstrates that the CAREX methodology can be readily adapted to different countries, economies, and priority carcinogens. CAREX exposure estimates are integral for informing primary prevention activities and improving estimates of the global occupational cancer burden.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.003 |
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".