Bibliographic record
Abstract
More than 50% of Canadians use natural health products such as vitamins, homeopathic remedies, traditional therapies and herbal medicines. Some herbal products have been well studied, others less so. Some are benign, while others have potential adverse effects, either alone or in combination with commonly prescribed pharmaceuticals. Health Canada has released several warnings concerning natural health products (www.hc-sc.gc.ca/english/warnings.htm). In 1999, Health Minister Allan Rock announced the creation of a new regulatory authority, the Office of Natural Health Products (www.hc-sc.gc.ca/hpb/onhp), to oversee herbal and traditional medicines. Its Web site includes a report of a 1999 conference setting its research agenda and its proposed regulatory framework for clinical trials involving natural health products. Levels of evidence are to be reviewed this fall. Online information on natural products is not only widely abundant but also widely variable in quality. Well-established resources include the National Center for Complementary and Alternative Medicine, which is run by the National Institutes of Health. It produces fact sheets and literature summaries (nccam.nih.gov). In conjunction with PubMed, NCCAM has developed a PubMed search configured for complementary and alternative therapies (www.nlm.nih.gov/nccam/camonpubmed.html). The Office of Dietary Supplements (ods.od.nih.gov) offers the International Bibliographic Information on Dietary Supplements database (ods.od.nih .gov/databases/ibids.html), which covers vitamins, minerals and selected biologic products in common use in North America. The Cochrane Collaboration (hiru.mcmaster.ca/cochrane) has reviewed evidence for the efficacy of established herbs such as St. John's wort. The Alternative Medicine Foundation maintains a database on herbal medicines, HerbMed (www.herbmed.org), which lists published evidence (whether clinical trial or longstanding folk use), warnings, preparations and mechanisms of action for commonly used herbs. On the American Cancer Society Web site (www.cancer.org), the menu-heading for complementary and alternative therapies links to patient information, while research, review and news articles can be found through the site search. For users of hand-held computers, files of “Common Herbs” and “Herbal Reference Guide” are available free from the Peripheral Brain site (pbrain.hypermart.net).
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.332 | 0.083 |
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".