Harmonization of Cancer and Noncancer Risk Assessment: Proceedings of a Consensus-Building Workshop
Bibliographic record
Abstract
Significant advancements have been made toward the use of all relevant scientific information in health risk assessments. This principle has been set forth in risk-assessment guidance documents of international agencies including those of the World Health Organization's International Programme on Chemical Safety, the U.S. Environmental Protection Agency, and Health Canada. Improving the scientific basis of risk assessment is a leading strategic goal of the Society of Toxicology. In recent years, there has been a plethora of mechanistic research on modes of chemical toxicity that establishes mechanistic links between noncancer responses to toxic agents and subsequent overt manifestations of toxicity such as cancer. The research suggests that differences in approaches to assessing risk of cancer and noncancer toxicity need to be resolved and a common broad paradigm for dose-response assessments developed for all toxicity endpoints. In November 1999, a workshop entitled "Harmonization of Cancer and Noncancer Risk Assessment" was held to discuss the most critical issues involved in developing a more consistent and unified approach to risk assessment for all endpoints. Invited participants from government, industry, and academia discussed focus questions in the areas of mode of action as the basis for harmonization, common levels of adverse effect across toxicities for use in dose-response assessments, and scaling and uncertainty factors. This report summarizes the results of those discussions. There was broad agreement, albeit not unanimous, that current science supports the development of a harmonized set of principles that guide risk assessments for all toxic endpoints. There was an acceptance among the participants that understanding the mode of action of a chemical is ultimately critical for nondefault risk assessments, that common modes of action for different toxicities can be defined, and that our approach to assessing toxicity should be biologically consistent.
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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 | 0.135 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.009 | 0.020 |
| Research integrity | 0.017 | 0.024 |
| 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".