The Global Meningococcal Initiative meeting on prevention of meningococcal disease worldwide: Epidemiology, surveillance, hypervirulent strains, antibiotic resistance and high-risk populations
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 2018 Global Meningococcal Initiative (GMI) meeting focused on evolving invasive meningococcal disease (IMD) epidemiology, surveillance, and protection strategies worldwide, with emphasis on emerging antibiotic resistance and protection of high-risk populations. The GMI is comprised of a multidisciplinary group of scientists and clinicians representing institutions from several continents. AREAS COVERED: Given that the incidence and prevalence of IMD continually varies both geographically and temporally, and surveillance systems differ worldwide, the true burden of IMD remains unknown. Genomic alterations may increase the epidemic potential of meningococcal strains. Vaccination and (to a lesser extent) antimicrobial prophylaxis are the mainstays of IMD prevention. Experiences from across the globe advocate the use of conjugate vaccines, with promising evidence growing for protein vaccines. Multivalent vaccines can broaden protection against IMD. Application of protection strategies to high-risk groups, including individuals with asplenia, complement deficiencies and human immunodeficiency virus, laboratory workers, persons receiving eculizumab, and men who have sex with men, as well as attendees at mass gatherings, may prevent outbreaks. There was, however, evidence that reduced susceptibility to antibiotics was increasing worldwide. EXPERT COMMENTARY: The current GMI global recommendations were reinforced, with several other global initiatives underway to support IMD protection and prevention.
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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 | 0.001 |
| 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 | 0.000 |
| 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