Opportunities and Challenges for Cost-Efficient Implementation of New Point-of-Care Diagnostics for HIV and Tuberculosis
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
Stakeholders agree that supporting high-quality diagnostics is essential if we are to continue to make strides in the fight against human immunodeficiency virus (HIV) and tuberculosis. Despite the need to strengthen existing laboratory infrastructure, which includes expanding and developing new laboratories, there are clear diagnostic needs where conventional laboratory support is insufficient. Regarding HIV, rapid point-of-care (POC) testing for initial HIV diagnosis has been successful, but several needs remain. For tuberculosis, several new diagnostic tests have recently been endorsed by the World Health Organization, but a POC test remains elusive. Human immunodeficiency virus and tuberculosis are coendemic in many high prevalence locations, making parallel diagnosis of these conditions an important consideration. Despite its clear advantages, POC testing has important limitations, and laboratory-based testing will continue to be an important component of future diagnostic networks. Ideally, a strategic deployment plan should be used to define where and how POC technologies can be most efficiently and cost effectively integrated into diagnostic algorithms and existing test networks prior to widespread scale-up. In this fashion, the global community can best harness the tremendous capacity of novel diagnostics in fighting these 2 scourges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it