Challenges and opportunities in the risk assessment of existing substances in Canada: lessons learned from the international community
Bibliographic record
Abstract
The evaluation and regulation of chemical substances have undergone a major overhaul in Canada, the USA and the European Union (EU) over the last decade. To facilitate increasing concerns over chemical safety, changes in regulations and strategic plans were introduced. Specifically, the Canadian parliament adopted a new amendment to the Canadian Environmental Protection Act (CEPA) in 1999, the US National Academy of Sciences published the 2007 NRC report TT21C, the US EPA developed the Strategic Plan in 2009, and the EU introduced new legislation in 2007 called Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH substances). A 2013 workshop held in Ottawa (Risk Sciences International) focused on regulatory issues and challenges faced by these nations. This review summarises many of the discussions held during the workshop and specifically, five challenges that Canada has encountered when assessing chemicals with limited data on Canada's Domestic Substances List (DSL).
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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 | 0.048 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".