Lab-in-a-pen: a diagnostics format familiar to patients for low-resource settings
Bibliographic record
Abstract
We present a low cost, simple and integrated device for medical diagnostics in low-resource settings called the lab-in-a-pen. Finger pricking, and sample collection and processing, are integrated with commercially available paper-based assays in a pen format. This approach ensures safety (i.e. biological sample and sharps containment) and can be used by untrained end users across multiple settings. The pen format also leverages existing low cost, high volume manufacturing and assembly methods. We characterize sample wicking in the lab-in-a-pen using porcine whole blood. The clinical diagnostic utility and usability of the lab-in-a-pen is established by testing of patients for Hepatitis B surface antigen (HBsAg) and Hepatitis B 'e' antigen (HBeAg) by medical staff at the National Hospital for Tropical Diseases in Hanoi, Vietnam.
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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".