Trends in NHP Research: Prospects and Challenges of Next Generation NHPs
Bibliographic record
Abstract
Modern Natural Health Products (NHPs) are medicinal dosage forms also known and regulated variously as Dietary Supplements, Phytomedicines and Complementary and Alternative Medicines in different countries. Related regulated food products include Medicinal Foods, Supplemented Foods, Functional Foods, and Nutraceuticals, while cannabis products are regulated separately. All of the above are derived from or inspired by natural products that have existed for millennia. Most have been developed through ancient medical systems (e.g. Traditional Chinese Medicine and Ayurveda) and distinct indigenous cultures, which combine worldview, beliefs, practices, into “ways of knowing”. Others were identified or advanced through scientific discovery and biotechnology. Together, they have contributed—and will continue to contribute—to human health and economy at a global scale.
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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 | 0.034 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".