Information Architecture Considerations in Designing a Comprehensive Tuberculosis Enterprise System in Western Kenya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Kenya ranks among the twenty-two countries that collectively contribute about 80% of the world's Tuberculosis cases; with a 50-200 fold increased risk of tuberculosis in HIV infected persons versus non-HIV hosts. Contemporaneously, there is an increase in mobile penetration and its use to support healthcare throughout Africa. Many are skeptical that such m-health solutions are unsustainable and not scalable. We seek to design a scalable, pervasive m-health solution for Tuberculosis care to become a use case for sustainable and scalable health IT in limited resource settings. We combine agile design principles and user-centered design to develop the architecture needed for this initiative. Furthermore, the architecture runs on multiple devices integrated to deliver functionality critical for successful Health IT implementation in limited resource settings. It is anticipated that once fully implemented, the proposed m-health solution will facilitate superior monitoring and management of Tuberculosis and thereby reduce the alarming statistic regarding this disease in this region.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it