New Perspectives on the Impact of BCG Vaccination on Bovine Tuberculosis Transmission: A Comprehensive Study Analysis
Bibliographic record
Abstract
The paper titled "BCG Vaccination Reduces Bovine Tuberculosis Transmission, Improving Prospects for Elimination," authored by Abebe Fromsa, Katriina Willgert, Sreenidhi Srinivasan, and others, was published in the journal Science on March 29, 2024. The research comes from the Aklilu Lemma Institute of Pathobiology at Addis Ababa University, the College of Veterinary Medicine and Agriculture at Addis Ababa University, and other institutions. This study focuses on the potential of the BCG vaccine to reduce the transmission of bovine tuberculosis (bTB) in Ethiopia. By integrating natural transmission experiments with mechanistic transmission models, the research aims to evaluate the effectiveness of the BCG vaccine in controlling bTB transmission under different herd conditions. Experimental results show that vaccinated animals exhibited a 74% reduction in bTB transmission compared to unvaccinated animals. This finding provides strong evidence supporting the BCG vaccine as an effective strategy for controlling bTB, especially in resource-limited settings.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".