Strengthening Tuberculosis Services for Children and Adolescents in Low Endemic Settings
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
In low tuberculosis-burden countries, children and adolescents with the highest incidence of tuberculosis (TB) infection or disease are usually those who have immigrated from high-burden countries. It is, therefore, essential that low-burden countries provide healthcare services to immigrant and refugee families, to assure that their children can receive proper testing, evaluation, and treatment for TB. Active case-finding through contact tracing is a critical element of TB prevention in children and in finding TB disease at an early, easily treated stage. Passive case-finding by evaluating an ill child is often delayed, as other, more common infections and conditions are suspected initially. While high-quality laboratory services to detect Mycobacterium tuberculosis are generally available, they are often underutilized in the diagnosis of childhood TB, further delaying diagnosis in some cases. Performing research on TB disease is difficult because of the low number of cases that are spread over many locales, but critical research on the evaluation and treatment of TB infection has been an important legacy of low-burden countries. The continued education of medical providers and the involvement of educational, professional, and non-governmental organizations is a key element of maintaining awareness of the presence of TB. This article provides the perspective from North America and Western Europe but is relevant to many low-endemic settings. TB in children and adolescents will persist in low-burden countries as long as it persists throughout the rest of the world, and these wealthy countries must increase their financial commitment to end TB everywhere.
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 | 0.001 | 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 it