Bibliographic record
Abstract
The success of researchers in developing innovative and effective medicines has produced a healthier and older population, as well as an observable shift in expenditure towards pharmaceuticals. In contrast to drug expenditures, patented drug prices have actually shown an average annual decrease of 0.5% since 1988. While we agree cost-effectiveness evaluation is a useful input into the decision-making process of drug benefit managers, it is but one consideration, and it is imperative that governments look beyond drug budgets to the broader benefits of innovative drug therapy to Canadians, both economically and clinically. The lead paper makes a number of suggestions regarding clinical trials that would lead to an increased demand on the developers of innovative medicines, all of which would raise the development costs of drugs while reducing the spectrum of available agents. This commentary argues that focusing greater attention on ensuring the appropriate use of medicines, with less concentration on restricting Canadians' access to effective drugs available in other countries, will yield the greatest benefits to the health of our population. Patient health management is a strategy that deserves a closer look to achieve this goal.
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 | 0.012 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.068 | 0.047 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".