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Record W2287470018 · doi:10.1080/21645515.2015.1052354

Current advances and challenges in the development of<i>Acinetobacter</i>vaccines

2015· article· en· W2287470018 on OpenAlexaff
Wangxue Chen

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsNational Research Council CanadaBrock University
Fundersnot available
KeywordsAcinetobacter baumanniiIntensive care medicineMultiple drug resistanceMedicineDrug developmentDrug resistanceImmunologyBiologyDrugMicrobiologyPseudomonas aeruginosaPharmacology

Abstract

fetched live from OpenAlex

Acinetobacter baumannii is a major cause of healthcare-associated infections worldwide with high morbidity and mortality. The clinical treatment of A. baumannii infections has become increasingly difficult because of the rapid emerging of multidrug and extremely drug resistant strains. Thus, there is an urgent need for the development of novel intervention strategies to combat this multidrug-resistant pathogen. Vaccine is one of the most effective medical measures for infection control and is likely to overcome the development of multidrug resistance by A. baumannii. Here we discussed the recent advances and potential challenges in development of A. baumannii vaccines with a focus on the 3 most important steps in the preclinical vaccine development: antigen selection, immune correlates of protection, and animal models for efficacy evaluation.

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)0.004
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.080
GPT teacher head0.319
Teacher spread0.239 · 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

Citations58
Published2015
Admission routes1
Has abstractyes

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