Cancer and the environment: Ten topics in environmental cancer epidemiology in Canada
Bibliographic record
Abstract
This Chronic Diseases in Canada supplement is a compilation of literature reviews by scientific experts. It was initiated as follow-up to the Green Plan, the federal government's environmental agenda in the 1990s. In recognizing that Canadians are concerned about the environment and its relationship to their health, this document attempts to address some of these concerns in relation to cancer by reviewing and summarizing the epidemiological literature for ten environmental exposures, and highlighting future research needs. The topics include three types of radiation exposure (ultraviolet, radon and electromagnetic (powerfrequency electromagnetic fields)), three classes of chemical exposure (organochlorines, disinfection by-products, and pesticides), two types of air pollution (environmental tobacco smoke and outdoor air pollution), and two industrial sources (pulp and paper milling, and metal mining and processing). This publication is intended to provide a base of information for researchers interested in environmental cancer epidemiology and to assist with the formulation of research priorities. The ten topics reviewed here were selected because concern about them has been expressed or because they involve known animal carcinogens. Complete elimination of exposures to carcinogens in the environment, synthetic or natural, is not technically feasible if cancer can potentially occur at any level of exposure (i.e., the linear non-threshold theory). Consequently, it is important to have an operational concept of safety which is more practical than that of zero risk. Such an approach uses the concept of acceptable or essentially negligible risk to determine the exposure levels at which carcinogens are regulated. Acceptable risk has been defined as one that is "so small, whose consequences are so slight, or whose associated benefits (perceived or real) are so great that persons or groups in society are willing to take or be subjected to that risk". The level of risk where remedial action is recommended will vary according to the "agent or process being regulated, the economic and social costs and benefits and technology factors". In accordance with the system used by the International Agency for Research on Cancer (IARC) to assess the strength of the evidence for human carcinogenicity, the ten exposures reviewed here can be grouped into three broad categories, with some exposures occupying more than one and the first category-human carcinogens-should be subdivided. Tables 1-4 refer to these categories. For many of the exposures discussed here, ongoing etiological research awaits methods development, particularly in exposure assessment.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.043 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".