Bibliographic record
Abstract
MPOX: Research priorities for threat reduction Concerted efforts are needed to close knowledge gaps around mpox to improve preparedness and response efforts for this neglected disease. Mpox, formerly known as monkeypox, is a previously neglected re-emerging zoonotic disease caused by monkeypox virus (MPV), genus Orthopoxvirus, family Poxviridae. This virus can cause severe illness in infected patients and is endemic in numerous countries across Central and West Africa, including the Democratic Republic of Congo (DRC), Nigeria, Cameroon, Sierra Leone, Ghana, Liberia, and others. However, in 2022, a global mpox outbreak led to the declaration of a public health emergency of international concern by the World Health Organization, with more than 90,000 confirmed cases reported from non-endemic global regions. While swift responses to this outbreak helped reduce case trends across highly impacted regions by Fall 2022, including the distribution of vaccine and therapeutics to at-risk communities, as well as increased public awareness, ongoing outbreaks in endemic regions continue to have deleterious effects on public health.
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 | 0.026 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.048 | 0.015 |
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".