Bibliographic record
Abstract
The Natural Health Products Regulations have been in force since January 1, 2004, and were put in place to help assure that Canadians have access to natural health products (NHPs) that are safe, effective and of high quality, while respecting freedom of choice and philosophical and cultural diversity. The Natural and Non-prescription Health Products Directorate (NNHPD) serves the regulatory function of providing oversight of non-prescription and disinfectant drugs in addition to NHPs. NHPs are defined in the Natural Health Products Regulations, as vitamins and minerals, herbal remedies, homeopathic medicines, traditional medicines, probiotics, and other products like amino acids and essential fatty acids. In order for NHPs to be licensed for sale in Canada, evidence supporting the safety, efficacy and quality of a natural health product is assessed by Health Canada. This presentation will provide an overview of the definition and scope of the Natural Health Products Regulations, with a focus on product classification. NNHPD participates in the classification of several products at the interface between NHPs and foods, medical devices, cosmetics and prescription drugs. Examples will be provided to illustrate the steps used to appropriately regulate different product types. Product classification at the food/NHP interface is based on several factors including product composition, representation, format, as well as public perception. Classification decisions are used to administer, monitor compliance with, and enforce the Food and Drugs Act and its regulations.
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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".