Ethical framework for observational studies of medicinal drug exposure in pregnancy
Bibliographic record
Abstract
BACKGROUND: The conduct of human research in the teratogenicity of drugs, chemicals, radiation and infections is needed in order to close critical gaps in knowledge. METHODS: We reviewed the various aspects of the ethics of conducting prospective human research in teratogenicity. RESULTS: Such research should respect the confidentiality of pregnant women and their families. Because this research is observational, interpretation of results is difficult, and the study design should strive to meet the highest possible scientific standards attainable in the particular research conditions. It should also be acknowledged that confidentiality cannot be always adhered to (e.g., if the interview reveals risks to minors). CONCLUSIONS: In general, the benefit risk ratio in this type of research is very favorable, although in specific cases the research follow-up may induce fears (e.g., drugs of abuse) in the woman being interviewed.
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.
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 | 0.646 | 0.623 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.018 | 0.018 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".