Editorials Shortages of medicines: a complex global challenge
Bibliographic record
Abstract
them generic injectable chemotherapy agents, are causing increasing concern in the United States of America (USA). 1,2 However, the problem is far wider, affecting other classes of medicines including injectable anaesthetic agents, such as propofol, intravenous nutrition and electrolyte products, enzyme replacement products and radiopharmaceuticals. 3–5 Medicine shortages have also been noted in Australia and Canada. 6,7 A recent commentary in a Belgian pharmacy journal claims that the problem is global – “from Afghanistan to Zimbabwe ” – listing 21 countries affected by a variety of supply problems. 8 A shortage of the injectable antibiotic streptomycin was reported in 15 countries in 2010, with 11 more countries predicting their stocks would run out before they could be replenished. 9 This problem does not seem to be that new: concern about prescription medicine shortages was raised in the USA at least a decade ago. 10 The American Society of Health-System Pharmacists ’ web site (available at:
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.023 | 0.014 |
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".