Elevated prevalence of malnutrition and malaria among school-aged children and adolescents in war-ravaged South Sudan
Bibliographic record
Abstract
Emerging as a sovereign state from decades of civil war, the Republic of South Sudan now faces poverty, a lack of health care infrastructure, a high burden of infectious diseases and a widespread food insecurity. School-aged children and youth, in particular, represent a high-risk demographic for malnutrition and infectious diseases. We screened 109 school-aged children and youth for nutritional status and malaria antigenaemia in Akuak Rak, South Sudan, and found a large proportion of underweight (77/109 = 73%) and prevalent malaria (44/109 = 40%). There was no significant association between malnutrition and malaria. This study represents one of the few published reports on child and youth nutritional status and malaria prevalence in South Sudan since its independence. The implementation of nutrition and malaria screening combined with evidence-based interventions in schools could help target this high burden vulnerable group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".