The Brighton collaboration standardized module for vaccine benefit-risk assessment
Bibliographic record
Abstract
Vaccine Benefit-Risk (B-R) assessment consists of evaluating the benefits and risks of a vaccine and making a judgment whether the expected key benefits outweigh the potential key risks associated with its expected use. B-R supports regulatory and public health decision-making throughout the vaccine's lifecycle. In August 2021, the Brighton Collaboration's Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Benefit-Risk Assessment Module working group was established to develop a standard module to support the planning, conduct and evaluation of structured B-R assessments for vaccines from different platforms, based on data from clinical trials, post-marketing studies and real-world evidence. It enables sharing of relevant information via value trees, effects tables and graphical depictions of B-R trade-offs. It is intended to support vaccine developers, funders, regulators and policy makers in high-, middle- or low-income countries to help inform decision-making and facilitate transparent communication concerning development, licensure, deployment and other lifecycle decisions.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".