High Sensitivity of Mobile Phone Microscopy Screening for Schistosoma haematobium in Azaguié, Côte d’Ivoire
Bibliographic record
Abstract
Schistosomiasis infections continue to impact African settings disproportionately, and there is an urgent need for novel tools to evaluate infection control and elimination strategies at the community level. Mobile phone microscopes are portable and semiautomated devices with multiple applications for screening neglected tropical diseases. In a community-based schistosomiasis screening program in Azaguié, Côte d'Ivoire, mobile phone microscopy demonstrated a sensitivity of 85.7% (95% CI: 69.7-95.2%) and specificity of 93.3% (95% CI: 87.7-96.9%) for Schistosoma haematobium identification compared with conventional light microscopy, and 95% sensitivity (95% CI: 74.1-99.8%) with egg concentrations of five or more per 10 mL of urine. Mobile phone microscopy is a promising tool for schistosomiasis control and elimination efforts.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".