Mutagenicity testing for chemical risk assessment: update of the WHO/IPCS Harmonized Scheme
Bibliographic record
Abstract
Since the publication of the International Programme on Chemical Safety (IPCS) Harmonized Scheme for Mutagenicity Testing, there have been a number of publications addressing test strategies for mutagenicity. Safety assessments of substances with regard to genotoxicity are generally based on a combination of tests to assess effects on three major end points of genetic damage associated with human disease: gene mutation, clastogenicity and aneuploidy. It is now clear from the results of international collaborative studies and the large databases that are currently available for the assays evaluated that no single assay can detect all genotoxic substances. The World Health Organization therefore decided to update the IPCS Harmonized Scheme for Mutagenicity Testing as part of the IPCS project on the Harmonization of Approaches to the Assessment of Risk from Exposure to Chemicals. The approach presented in this paper focuses on the identification of mutagens and genotoxic carcinogens. Selection of appropriate in vitro and in vivo tests as well as a strategy for germ cell testing are described.
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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 | 0.108 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.013 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".