Implications of subclinical tuberculosis for vaccine trial design and global effect
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 is a leading cause of death from an infectious agent globally. Infectious subclinical tuberculosis accounts for almost half of all tuberculosis cases in national tuberculosis prevalence surveys, and possibly contributes to transmission and might be associated with morbidity. Modelling studies suggest that new tuberculosis vaccines could have substantial health and economic effects, partly based on the assumptions made regarding subclinical tuberculosis. Evaluating the efficacy of prevention of disease tuberculosis vaccines intended for preventing both clinical and subclinical tuberculosis is a priority. Incorporation of subclinical tuberculosis as a composite endpoint in tuberculosis vaccine trials can help to reduce the sample size and duration of follow-up and to evaluate the efficacy of tuberculosis vaccines in preventing clinical and subclinical tuberculosis. Several design options with various benefits, limitations, and ethical considerations are possible in this regard, which would allow for the generation of the evidence needed to estimate the positive global effects of tuberculosis vaccine trials, in addition to informing policy and vaccination strategies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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