Bibliographic record
Abstract
All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Canadian Medical Association. The cover of Time Magazine on Sept. 14, 1994, read“Revenge of the killer microbe ” in reference to an ar-ticle about emerging infections, including drug-re-sistant bacteria that are difficult to treat.1 A lead article in Science just 2 years earlier cautioned readers about the pos-sibility of a “post-antibiotic era ” and stressed the impor-tance of the discovery of new drugs and the prudent use of currently available antimicrobials.2 The mantra of the ills of antibiotic overuse has been repeated in the medical and lay press over the past 10–15 years. It is clear from ecologic studies that antibiotic use is a driv-ing force in the emergence of antibiotic-resistant organisms in community and hospital settings. Both the inappropriate use of antibiotics for viral respiratory tract infections and the overuse of powerful, broad-spectrum antibiotics contribute substantially to this problem. Despite the long-term trend of
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 | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.024 | 0.018 |
| Insufficient payload (model declined to judge) | 0.079 | 0.041 |
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".