All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Canadian Medical Association. Commentary
Bibliographic record
Abstract
Among the functions of public health are health protection (e.g., food and water safety, basic sanitation), disease and injury preven-tion (including vaccinations and outbreak management), popula-tion health assessment; disease and risk factor surveillance; and health promotion.1 In the early 20th century, public health was well recog-nized as a major factor in ensuring the health of thecommunity. Infectious diseases such as influenza, diph-theria, tuberculosis and polio cut wide swaths through the population, striking fear into the hearts of the afflicted and their families, as well as the physicians providing care. Mil-lions died, including thousands of Canadians who suc-cumbed to the “Spanish flu ” (the influenza pandemic of 1918). Infants and children were particularly affected by diphtheria, gastroenteritis and polio. Bringing many of these killers under control through public health programs was hailed as one of the greatest accomplishments of medi-
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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.103 | 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".