The origins of malaria: there are more things in heaven and earth …
Bibliographic record
Abstract
SUMMARY Malaria remains one of the most significant global public health burdens, with nearly half of the world's population at risk of infection. Malaria is not however a monolithic disease - it can be caused by multiple different parasite species of the Plasmodium genus, each of which can induce different symptoms and pathology, and which pose quite different challenges for control. Furthermore, malaria is in no way restricted to humans. There are Plasmodium species that have adapted to infect most warm-blooded vertebrate species, and the genus as a whole is both highly successful and highly diverse. How, where and when human malaria parasites originated from within this diversity has long been a subject of fascination and sometimes also controversy. The past decade has seen the publication of a number of important discoveries about malaria parasite origins, all based on the application of molecular diagnostic tools to new sources of samples. This review summarizes some of those recent discoveries and discusses their implication for our current understanding of the origin and evolution of the Plasmodium genus. The nature of these discoveries and the manner in which they are made are then used to lay out a series of opportunities and challenges for the next wave of parasite hunters.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".