Risk and Benefit of Drug Use During Pregnancy
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
Environmental teratogenic factors (e.g. alcohol) are preventable. We focus our analysis on human teratogenic drugs which are not used frequently during pregnancy. The previous human teratogenic studies had serious methodological problems, e.g. the first trimester concept is outdated because environmental teratogens cannot induce congenital abnormalities in the first month of gestation. In addition, teratogens usually cause specific congenital abnormalities or syndromes. Finally, the importance of chemical structures, administrative routes and reasons for treatment at the evaluation of medicinal products was not considered. On the other hand, in the so-called case-control epidemiological studies in general recall bias was not limited. These biases explain that the teratogenic risk of drugs is exaggerated, while the benefit of medicine use during pregnancy is underestimated. Thus, a better balance is needed between the risk and benefit of drug treatments during pregnancy. Of course, we have to do our best to reduce the risk of teratogenic drugs as much as possible, however, it is worth stressing the preventive effect of drugs for maternal diseases (e.g. diabetes mellitus and hyperthermia) related congenital abnormalities.
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 | 0.001 | 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 it