A different approach to validating screening assays for developmental toxicity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There continue to be many efforts around the world to develop assays that are shorter than the traditional embryofetal developmental toxicity assay, or use fewer or no mammals, or use less compound, or have all three attributes. Each assay developer needs to test the putative assay against a set of performance standards, which traditionally has involved testing the assays against a list of compounds that are generally recognized as "positive" or "negative" in vivo. However, developmental toxicity is highly conditional, being particularly dependent on magnitude (i.e. dose) and timing of exposure, which makes it difficult to develop lists of compounds neatly assigned as developmental toxicants or not. APPROACH: Here we offer an alternative approach for the evaluation of developmental toxicity assays based on exposures. Exposures are classified as "positive" or "negative" in a system, depending on the compound and the internal concentration. Although this linkage to "internal dose" departs from the recent approaches to validation, it fits well with widely accepted principles of developmental toxicology. CONCLUSIONS: This paper introduces this concept, discusses some of the benefits and drawbacks of such an approach, and lays out the steps we propose to implement it for the evaluation of developmental toxicity assays.
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.
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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it