ABCDXXX: The obscenity of postmarketing surveillance for teratogenic effects
Bibliographic record
Abstract
Our current system of postmarketing surveillance, which is based on voluntary reporting of suspected teratogenic effects, is a failure. Postmarketing surveillance should, at a minimum, provide reassurance that every approved drug treatment does not produce a teratogenic effect as great as thalidomide embryopathy or fetal alcohol syndrome. This means that postmarketing surveillance should be able to detect a twofold or greater increase in the frequency of major congenital anomalies, a fivefold or greater increase in the frequency of intellectual disability, or a characteristic pattern of minor anomalies and functional abnormalities that occurs with a frequency of at least 10% among the children of women who were treated with the drug during pregnancy. Effective surveillance for teratogenic effects could be accomplished through a complementary set of mechanisms that includes pregnancy exposure registries or cohorts as well as direct examination of a small subset of infants whose mothers received the treatment during various periods of pregnancy. If this routine surveillance reveals a "signal" (i.e., an indication suggesting a possible teratogenic effect), further study would be needed to establish whether the observed effect is real and causal. Once a signal of possible teratogenicity in humans has been recognized, validating or refuting it would become an urgent matter.
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 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 | 0.009 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".