Assessment of fetal and neonatal outcomes in the offspring of women who had been treated with dried ginger (<i>Zingiberis rhizoma siccus</i>) for a variety of illnesses during pregnancy
Bibliographic record
Abstract
The present study was designed to investigate if exposure to dried ginger during pregnancy would increase the risk of adverse fetal and neonatal outcomes. Participants consisted of 159 singleton pregnant women who received dried ginger as a herbal medication. We also included a control group of 306 pregnant women who had not been exposed to any herbal medication or any known teratogen. No increased risk of major malformations was detected in exposed women (OR = 4.9; 95% CI 0.9-25.5; p = 0.051). The incidence of stillbirths in the exposed group was marginally higher than in the controls (OR = 7.8; 95% CI 0.9-70.3; p = 0.05). The risk was more evident when the exposed group was compared with the general population in the Republic of Korea (OR = 7.9; 95% CI 2.9-21.4; p < 0.0001). Other fetal and neonatal study outcomes investigated in the exposed group were similar (p > 0.05) to the controls. In conclusion, dried ginger does not appear to be a major teratogen. However, due to the limitations of the study, e.g. the large variability in the dose of dried ginger in the exposed group, as well as the concomitant exposure to other herbal medications, the increased incidence of stillbirths requires confirmation in larger cohort studies.
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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 | 0.001 | 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) | 0.001 | 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 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".