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Record W2604770723 · doi:10.1080/14760584.2017.1308828

Emerging experience with meningococcal serogroup B protein vaccines

2017· review· en· W2604770723 on OpenAlexaboutno aff
Daniela Toneatto, Mariagrazia Pizza, Vega Masignani, Rino Rappuoli

Bibliographic record

VenueExpert Review of Vaccines · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsnot available
FundersGlaxoSmithKline BiologicalsGlaxoSmithKlinePfizer
KeywordsMeningococcal vaccineMedicineImmunogenicityMeningococcal diseaseHerd immunityVaccinationCarriageClinical trialNeisseria meningitidisVirologyTransmission (telecommunications)LicensureIntensive care medicineImmunologyBiologyImmunizationImmune systemComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The successful development of two broadly protective vaccines targeting Neisseria meningitidis serogroup B (MenB); 4CMenB and rLP2086, is the most significant recent advance in meningococcal disease prevention. Areas covered: Here we review the principles underlying the development of each vaccine and the novel methods used to estimate vaccine coverage. We update clinical and post-licensure experience with 4CMenB and rLP2086. Expert commentary: The immunogenicity and acceptable safety profile of 4CMenB and rLP2086 has been demonstrated in clinical trials. Continuing uncertainties exist around the appropriate age groups to be immunized, the degree and duration of efficacy, and the impact on nasopharyngeal carriage which has implications for strategies to interrupt transmission and maximize herd protection effects. Universal vaccination programs such as those undertaken in Quebec and the United Kingdom are providing important information on these issues. The potential for MenB vaccines to prevent infection by other serogroups appears promising, and the impact of MenB vaccines on other pathogenic neisserial species with similar surface proteins warrants further investigation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.050
GPT teacher head0.383
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations69
Published2017
Admission routes1
Has abstractyes

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