Categorization of Chemicals According to Their Relative Human Skin Sensitizing Potency
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
Although adoption of skin sensitization in vivo assays for hazard identification is likely to be successful in the next few years, this does not replace their use in potency prediction. Notably, measurement of potency of skin sensitizers in the local lymph node assay has been important. However, this local lymph node assay potency measure has not been formally assessed against a range of substances of known human sensitizing potential, because the latter is lacking. Accordingly, criteria for human data have been established that characterize 6 categories of human sensitizing potency, with 1 the most potent and 5 the least potent; category 6 represents true nonsensitizers. The literature has been searched, and 131 chemicals assigned into these categories according to their intrinsic potency judged only by the available human information. The criteria and data set generated provide a basis for examination of the capacity of nonanimal approaches for the determination of human sensitization potency.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 it