Host Genomics and Control of Tuberculosis Infection
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
Tuberculosis (TB), caused by the human pathogenic bacterium Mycobacterium tuberculosis, poses a major global health problem. The tubercle bacillus is transmitted from person to person by aerosol, but only a proportion of those in contact with infectious aerosol particles will become infected. If infection occurs, less than 10% of those infected will develop clinical signs of TB, while the majority will develop latent TB infection (LTBI). The identification and treatment of LTBI persons is a major aspect of TB control, especially in low-incidence, highly developed nations. In the absence of a gold standard test for latent TB, infection is inferred with the help of either the in vivo tuberculin skin test or in vitro interferon gamma release assays of anti-mycobacterial immunity. Recent work has observed high heritability of these immune assays indicating the critical role of the host genetic background on the establishment of infection and latency. Additional genetic studies have identified the host genetic background as an important covariate for the proper interpretation of the results obtained from LTBI assays. Taken together, these data suggest TB surveillance and control can likely be improved by including host genetic information into the interpretation of these widely used assays.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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