Bibliographic record
Abstract
Pharmaceuticals account for the fastest growing component of health care costs in Canada, with average growth rates that are 3 times the annual rate of inflation. The Patented Medical Prices Review Board (PMPRB) says the growth is caused primarily by increased use and rapid uptake of new therapies. Sales of patented drugs for human use totalled $6.3 billion in 2000, a 16.7% increase over 1999. In 2000 these sales represented 63% of all drug expenditures for human use. Between 1995 and 1998, sales of patented drugs for both human and veterinary use, as a proportion of total drug sales, increased from 43.9% to 55.1% of total spending. The PMPRB was created by the federal government to ensure that patent holders do not charge excessive prices during the period of patent protection. In every year since 1998 (except 1992), price increases for patented drugs have been less than increases in the Consumer Price Index (CPI). In 2000, the CPI increased by 2.7%; according to a price index developed by the PMPRB, prices for patented drugs rose by 0.4% during the same period. Canada continues to have lower prices for patented drugs than many other industrialized countries. In 2000, prices in Sweden, Germany, the United Kingdom, Switzerland and the United States were all higher than in Canada, while prices in France and Italy were lower.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.155 | 0.031 |
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".