New Directions in Toxicity Testing
Bibliographic record
Abstract
In 2007, the U.S. National Research Council (NRC) published a groundbreaking report entitled Toxicity Testing in the 21st Century: A Vision and a Strategy. The purpose of this report was to develop a long-range strategic plan to update and advance the way environmental agents are tested for toxicity. The vision focused on the identification of critical perturbations of toxicity pathways that lead to adverse human health outcomes using modern scientific tools and technologies. This review describes how emerging scientific methods will move the NRC vision forward and improve the manner in which the potential health risks associated with exposure to environmental agents are assessed. The new paradigm for toxicity testing is compatible with the widely used four-stage risk assessment framework originally proposed by the NRC in 1983 in the so-called Red Book. The Nrf2 antioxidant pathway provides a detailed example of how relevant pathway perturbations will be identified within the context of the new NRC vision for the future of toxicity testing. The implications of the NRC vision for toxicity testing for regulatory risk assessment are also discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.004 | 0.012 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".