Editorial: Women in developmental and reproductive toxicology: 2021
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
Women remain a minority group in toxicology, both as lead investigators and in terms of using the tools of toxicology to understand environmental influences on women's health. While the fields of toxicology and environmental medicine are diversifying, underrepresented groups, including women and women of color, face unique challenges. When unmet, this can lead to isolation, lack of support, career dissatisfaction, and ultimately higher rates of attrition. This special issue was therefore conceived to highlight the work of women toxicologists to emphasize their unique mentorship and support needs, and to maximize career success. Given this focus, the scientific work primarily addresses women and child health (i.e., pregnancy and health of the next generation). This special issue contains two original data papers, a mini-review, and a perspective piece on what is needed to support and mentor women in what remains a male-dominated field.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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