Teratology public affairs committee position paper: Maternal obesity and pregnancy
Bibliographic record
Abstract
Compared to normal-weight women, obese women have an increased risk of infertility and pregnancy complications. The most consistently described pregnancy complications are hypertensive disorders, gestational diabetes mellitus, thromboembolic events, and cesarean section. Fetal and neonatal complications may include congenital malformations, macrosomia, and shoulder dystocia. The literature suggests that women with a body mass index (BMI) >or=30 have approximately double the risk of having a child with a neural tube defect (NTD) compared to normal-weight women, and the increased risk associated with higher maternal body weight does not appear to be modified by folic acid supplementation. The Public Affairs Committee of the Teratology Society supports the public health initiatives identified by the U.S. Food and Drug Administration in 2004 and the research initiatives identified by the National Institutes of Health in 2004. The Public Affairs Committee recommends that clinicians counsel women about appropriate caloric intake and exercise and that health-care providers educate parents about appropriate childhood nutrition. Breast-feeding should be encouraged based on evidence of a protective effect against childhood obesity, as well as other health advantages.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".