All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Canadian Medical Association. CMAJ Commentary © 2009 Canadian Medical Association or its licensors Online-1
Bibliographic record
Abstract
The fact that 1 of the main treatment modalities in healthcare — prescription drugs used outside the hospital set-ting — remains outside the medicare envelope in 2009 perplexes many clinicians, academics and the general public. Canada has an overall public health care system, but the lack of coverage for prescription drugs is a gaping hole in the system with adverse consequences for many Canadians. Moreover, Canada lags behind many comparator nations in issues related to prescription access and affordability, the quality and safety of medication use, and the use of technologies such as e-prescribing that would help to improve the system (Table 1).1–3 The National Pharmaceuticals Strategy, part of the federal, provincial and territorial health accord signed in 2004,4 was an attempt for the participating governments to jointly develop and implement drug policy solutions. More specifically, the prime minister and premiers directed their health ministers to focus on 9 specific action items that dealt with issues related to access
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 | 0.003 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.018 | 0.014 |
| Insufficient payload (model declined to judge) | 0.157 | 0.072 |
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".