CAREX CANADA: OCCUPATIONAL AND ENVIRONMENTAL CARCINOGEN SURVEILLANCE
Bibliographic record
Abstract
Background and Aims: CAREX was created by the Finnish Institute for Occupational Health in the 1990s. It raised awareness regarding occupational cancer, is widely quoted, and used to assess the impact of workplace carcinogens. In 2008 we launched CAREX Canada as a population level occupational and environmental surveillance project. The objectives of the project are to identify how many people are exposed, how and where they are exposed, and their level of exposure. Methods: CAREX Canada adopted the general approach of the original CAREX project for occupational carcinogens, although estimates are produced at a finer level of resolution and groups (based on industry/occupation) are flagged for potential exposures greater than half the occupational limit. Several different approaches were taken for environmental exposures, including spatial modeling and general risk assessment using published measured concentrations. Environmental estimates were converted into benzene equivalent doses or population-level cancer risks in order to compare the relative contribution from various sources or different exposures. Results: To date we have assessed exposure to 50 occupational and 30 environmental known and suspected carcinogens. The 10 most common occupational are shift work, solar radiation, diesel exhaust, other PAH-related exposures, silica, benzene, wood dust, lead, asbestos and chromium. In the environment, highest estimated lifetime excess cancer risks (>100/million) were due to formaldehyde (indoor air) and diesel particulates (outdoor air). Elevated risks (>10/million-<100/million) were also predicted for diesel particulates, acetaldehyde, benzene, 1,3-butadiene and total chromium (indoor air); arsenic, chloroform, hexavalent chromium and bromodichloromethane (drinking water); and arsenic (food). Traffic, residential wood burning, and industrial emitters dominate emissions in watersheds and ecoregions. Conclusions: CAREX Canada is the first program of its kind in Canada. It is raising awareness of the importance of occupational and environmental cancer, providing essential data for prevention, and is already being used for surveillance, risk assessment, and epidemiology.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".