The Value of Tiered Chemical Toxicity Testing
Bibliographic record
Abstract
Most of the chemicals to which humans are exposed have not been assessed for human health risk. This is largely owed to the time- and cost-prohibitive nature of traditional chemical toxicity tests. Fortunately, there exist simpler alternatives to traditional testing. In a tiered testing scheme— where tests are performed in order of increasing complexity— savings can be realized by not proceeding with more complex tests when simpler tests suffice. Here, we extend to a tiered testing setting a Value of Information framework for weighing trade-offs in the timeliness, cost, and uncertainty reduction of chemical toxicity tests. A “stopping rule” is established and we see that, across 45 hypothetical but realistic scenarios, the expected value of the tiered testing scheme consistently exceeds that of individual tests. As we enter a new era of toxicity testing, VOI-governed tiered testing is a promising avenue for guiding the implementation of time- and cost-effective tests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".