White Paper: Pathways to Progress in Newborn Screening for Sickle Cell Disease in Sub-Saharan Africa
Bibliographic record
Abstract
Sickle Cell Disease (SCD) is among the most common single-gene diseases in the world but evidence-based comprehensive health care has not been implemented where the highest prevalence of SCD occurs, in sub-Saharan Africa (SSA). It represents an urgent health burden, both in terms of mortality and morbidity with an estimated mortality of 8-16% in children under 5 years in SSA. Addressing the high mortality of SCD in SSA and for effective management of SCD, newborn screening (NBS) should be incorporated with prevention of infections (including pneumococcal septicaemia and malaria), parental education and support at all levels of healthcare provision to enable timely recognition. The NBS working group of the Africa Sickle Cell Research Network (AfroSickleNet) collaboration surveyed current projects in NBS in SSA, and current conditions that hinder more widespread implementation of NBS for SCD. Solutions based on new point-of-care testing technology to disseminate education, and implementation science approaches that leverage existing resources are proposed.
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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 | 0.019 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".