21st Century Approaches for Evaluating Exposures, Biological Activity, and Risks of Complex Substances: Workshop highlights
Bibliographic record
Abstract
The June 2019 workshop 21st Century Approaches for Evaluating Exposures, Biological Activity, and Risks of Complex Substances, co-organised by the International Council of Chemical Association's Long-Range Research Initiative and the European Commission's Joint Research Centre, is summarised. Focus was the need for improved approaches to evaluate the safety of complex substances. Approximately 10% and 20% of substances registered under the EU chemicals legislation are 'multi-constituent substances' and 'substances of unknown or variable compositions, complex reaction products and biological substances' (UVCBs), respectively, and UVCBs comprise approximately 25% of the U.S. Toxic Substances Control Act Inventory. Workshop participants were asked to consider how the full promise of new approach methodologies (NAMs) could be brought to bear to evaluate complex substances. Sessions focused on using NAMs for screening, biological profiling, and in complex risk evaluations; improving read-across approaches employing new data streams; and methods to evaluate exposure and dosimetry. The workshop concluded with facilitated discussions to explore actionable steps forward. Given the diversity of complex substances, no single 'correct' approach was seen as workable. The path forward should focus on 'learning by doing' by developing and openly sharing NAM-based fit-for-purpose case examples for evaluating biological activity, exposures and risks of complex substances.
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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 | 0.062 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.012 | 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".