Rapid Screening of Lower Concern Substances for Human Health Screening Assessments under the Canadian Environmental Protection Act (CEPA 1999)
Bibliographic record
Abstract
Background The rapid screening approach facilitates the further prioritization of substances for assessment under the Canadian Environmental Protection Act, 1999 (CEPA 1999) by rapidly identifying those substances that may have a higher or lower potential for concern based on hazard or exposure considerations. The approach also helps focus resources on higher priority substances by rapidly identifying those that are not of concern. Methods and Results Given the reported quantities in commerce in Canada (? 1000 kg) of these substances, indirect exposure to the general population from environmental media (air, water, soil) is not expected to be significant. Certain uses, may however, result in direct exposure. The term “direct use” refers to the use of a chemical substance that is directly, or as part of a mixture, a product, or a manufactured item, sold to or made available to Canadians for their use. A user is considered to be anyone from the general public who has access to a product that is advertised, imported or sold in Canada. To determine if a substance is used in, or present in a product used by Canadians, a number of domestic and international resources were consulted. Based on information identified from these sources, as well as other available information on the substance, it was determined that substances with the potential for direct exposure to the general population include those that are present, either intentionally or unintentionally, in products or manufactured items that are commonly used by Canadians. Using this rapid screening approach the Government of Canada was able to identify, and conduct a screening assessment for over 500 substances Conclusion The rapid screening approach has demonstrated that it can be used as a mechanism to efficiently deal with large numbers of substances in an efficent, timely, and scientifically defensible manner, while meeting the requirements under CEPA (1999) to conduct screening assessments for substances which met the categorization criteria set out in the Act.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".