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Record W2463552586 · doi:10.1128/cvi.00230-16

Summary and Recommendations from the National Institute of Allergy and Infectious Diseases (NIAID) Workshop “Gonorrhea Vaccines: the Way Forward”

2016· review· en· W2463552586 on OpenAlexaff
Lee M. Wetzler, Ian M. Feavers, Scott D. Gray‐Owen, Ann E. Jerse, Peter A. Rice, Carolyn Deal

Bibliographic record

VenueClinical and Vaccine Immunology · 2016
Typereview
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious Diseases
KeywordsGonorrheaMedicineVirology

Abstract

fetched live from OpenAlex

UNLABELLED: There is an urgent need for the development of an antigonococcal vaccine due to the increasing drug resistance found in this pathogen. The U.S. Centers for Disease Control (CDC) have identified multidrug-resistant gonococci (GC) as among 3 "urgent" hazard-level threats to the U.S. POPULATION: In light of this, on 29 to 30 June 2015, the National Institute for Allergy and Infectious Diseases (NIAID) sponsored a workshop entitled "Gonorrhea Vaccines: the Way Forward." The goal of the workshop was to gather leaders in the field to discuss several key questions on the current status of gonorrhea vaccine research and the path forward to a licensed gonorrhea vaccine. Representatives from academia, industry, U.S. Government agencies, and a state health department were in attendance. This review summarizes each of the 4 scientific sessions and a series of 4 breakout sessions that occurred during the one and a half days of the workshop. Topics raised as high priority for future development included (i) reinvigoration of basic research to understand gonococcal infection and immunity to allow intervention in processes essential for infection; (ii) clinical infection studies to establish parallels and distinctions between in vitro and animal infection models versus natural human genital and pharyngeal infection and to inform in silico modeling of vaccine impact; and (iii) development of an integrated pipeline for preclinical and early clinical evaluation and direct comparisons of potential vaccine antigens and adjuvants and routes of delivery.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0470.029

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 head0.065
GPT teacher head0.395
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations43
Published2016
Admission routes1
Has abstractyes

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