Health Risks Over the Internet: Advice Offered by "Medical Herbalists" to a Pregnant Woman
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to investigate Internet advice offered by "medical herbalists" to a pregnant woman regarding herbal treatment of morning sickness. STUDY DESIGN: Search engines were used to find relevant Web sites and all potential e-mail addresses were contacted. Herbalists were asked for advice regarding three specific medicinal herbs: ginger, raspberry and juniper. RESULTS: Eighty-three e-mail addresses were found and contacted. The response rate was 51%. Nineteen (45%) of all respondents recommended ginger, 9 (21%) of them without mentioning adverse effects. Seven (17%) respondents recommended taking raspberry; five (12%) without mentioning adverse effects. No respondent recommended taking juniper during pregnancy and 12 herbalists (29%) warned about using this herbal remedy during pregnancy. CONCLUSIONS: Advice about herbal medicine is readily available over the Internet. The advice offered is misleading at best and dangerous at worst. Potential Internet users should be made aware of these problems and ways of minimizing the risk should be found.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".