Bibliographic record
Abstract
Saunders MJ, Wingfield T, Tovar MA, et al. A score to predict and stratify risk of tuberculosis in adult contacts of tuberculosis index cases: a prospective derivation and external validation cohort study. Lancet Infect Dis 2017; 17: 1090–99—The support and grants in the Acknowledgments section should have been assigned as follows: This study was supported by Wellcome Trust awards 057434/Z/99/B (MAT, KZ, RM, TRV, JSF, RHG, and CAE), Z070005/Z/02/Z (MAT, TRV, JSF, RHG, and CAE), 078340/Z/05/Z (MAT, KZ, RM, TRV, JSF, and RHG, CAE), 105788/Z/14/Z (SD, RHG, and CAE), 201251/Z/16/Z (MJS, RHG, and CAE), the Department for International Development Civil Society Challenge Fund (MAT, KZ, RM, TRV, CAE), the Joint Global Health Trials consortium (Medical Research Council, Department for International Development, and Wellcome Trust award MR/K007467/1 [TW, MAT, KZ, RM, TRV, RHG, and CAE]), the Bill & Melinda Gates Foundation (award OPP1118545 [TW, MAT, RM, TRV, and CAE]), Imperial College National Institutes of Health Research Biomedical Research Centre (JAF and CAE), the Foundation for Innovative New Diagnostics (MAT, KZ, TRV, and CAE), the Sir Halley Stewart Trust (CAE), WHO (CAE), the STOP TB partnership's TB REACH initiative funded by the Government of Canada (W5_PER_CDT1_PRISMA [MAT, RM, and CAE]), and Innovation For Health And Development (MJS, TW, and CAE).
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.642 | 0.442 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".