Dossier : Les produits de santé naturels - Perspective et enjeux pour la pratique - Partie 1
Bibliographic record
Abstract
Resume Les produits de sante naturels (PSN) existent depuis longtemps. On rapporte que les ventes canadiennes des 50 000 PSN etaient d’environ 4,3 milliards de dollars en 2002-2003¹. En comparaison, les ventes canadiennes de tous les medicaments pour usage humain etaient de 15,9 milliards de dollars en 2004². Le nombre de produits inclus dans la base de donnees sur les produits pharmaceutiques est de plus de 24 000³. Depuis janvier 2004, le Canada s’est dote d’un Reglement sur les produits de sante naturels sous l’egide de la Loi sur les aliments et drogues . L’objectif de ce dossier est de presenter une perspective des produits de sante naturels au Canada et d’identifier les enjeux pour les pharmaciens oeuvrant en etablissements de sante. Ce dossier est presente en deux parties. La premiere partie presente une mise en contexte reglementaire, une description de l’utilisation actuelle des produits de sante naturels au Canada et des aspects ethiques en ce qui concerne leur utilisation. Abstract Natural healthcare products have existed for a long time. In 2002–2003 the sales estimates in Canada of approximately 50,000 natural health care products approached $4.3 billion.¹˒ In comparison, the total sales in 2004 of all medication for human consumption in Canada was $15.9 billion. Today more than 240,000 products are included in the drug product database.³ Consequently, after January 2004, Canada adopted the Natural Health Products Regulations, falling under the Food and Drugs Act. The purpose of this report, a two-part series, is to provide a perspective on the role of natural health products in Canada and to identify potential challenges for the hospital pharmacist. The first part will provide a review of regulations governing natural healthcare products, it will describe natural healthcare product utilization, and it will discuss some of the ethical concerns surrounding their use.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".