Development of Systematic Reviews to Inform WHO’s Recommendations for Elimination and Prevention of Re-Establishment of Malaria: Methodology
Bibliographic record
Abstract
The basis for an evidence-based recommendation is a well-conducted systematic review that synthesizes the primary literature relevant to the policy or program question of interest. In 2020, the WHO commissioned 10 systematic reviews of potential interventions in elimination or post-elimination settings to summarize their impact on malaria transmission. This paper describes the general methods used to conduct this series of systematic reviews and notes where individual reviews diverged from the common methodology. The paper also presents lessons learned from conducting the systematic reviews to make similar future efforts more efficient, standardized, and streamlined.
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 | 0.484 | 0.647 |
| Meta-epidemiology (narrow) | 0.009 | 0.008 |
| Meta-epidemiology (broad) | 0.019 | 0.023 |
| Bibliometrics | 0.045 | 0.029 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.011 | 0.010 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".