The Global Meningococcal Initiative: global epidemiology, the impact of vaccines on meningococcal disease and the importance of herd protection
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
INTRODUCTION: The 2015 Global Meningococcal Initiative (GMI) meeting discussed the global importance of meningococcal disease (MD) and its continually changing epidemiology. Areas covered: Although recent vaccination programs have been successful in reducing incidence in many countries (e.g. Neisseria meningitidis serogroup [Men]C in Brazil, MenA in the African meningitis belt), new clones have emerged, causing outbreaks (e.g. MenW in South America, MenC in Nigeria and Niger). The importance of herd protection was highlighted, emphasizing the need for high vaccination uptake among those with the highest carriage rates, as was the need for boosters to maintain individual and herd protection following decline of immune response after primary immunization. Expert commentary: The GMI Global Recommendations for Meningococcal Disease were updated to include a recommendation to enable access to whole-genome sequencing as for surveillance, guidance on strain typing to guide use of subcapsular vaccines, and recognition of the importance of advocacy and awareness campaigns.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it