Editorial: Drug development of herbal medicines: Regulatory perspectives
Bibliographic record
Abstract
The global trade of medicinal plants and their derivatives was estimated at US$33 billion in 2014, and the World Health Organization has estimated that it will increase to US$50 trillion by 2050. Different regulatory frameworks and categories at the national and regional levels describe medicinal plants either as mainstream therapy or as complementary and alternative medicines. The resulting complex terminology has seen medicinal plants classified as medicines (Australia), herbal medical products (European Union), botanicals (United States), and natural health products (Canada). In China, there is a distinction between traditional Chinese medicine (TCMs) and natural medicinal products. In India, traditional medicine is separated into three systems: Ayurveda, Unani, and Siddha. In Japan, Kampo medicines are classified as pharmaceutical drugs, and in Thailand, as part of the primary health care system. Many national health authorities have established guidelines and regulations concerning the quality, efficacy, and safety profiles of these products. Five papers are included in this Research Topic, all of which concern these three fundamental aspects of the health properties of herbal medicines.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".