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Record W2067496779 · doi:10.2174/13892010113146660230

Challenges and Opportunities for Bacterial Vaccine Development in the 21<sup>st</sup> Century

2014· review· en· W2067496779 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Pharmaceutical Biotechnology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicvaccines and immunoinformatics approaches
Canadian institutionsResearch Manitoba
Fundersnot available
KeywordsProteomicsInformaticsGenomicsComputational biologyBiologyBiotechnologyBioinformaticsGenomePolitical scienceGenetics

Abstract

fetched live from OpenAlex

With the convergence of modern technology in genomics, proteomics, carbohydrate, protein and lipid biochemistry as well as decades of experience in vaccine development and delivery of immunization programs, the Global Vaccine Action Plan has declared 2011 to 2020 as 'The Decade of Vaccines'. This review focuses on bacterial vaccines and summarises the current state of vaccinology in bacteriology and looks forward to the potential of how the newer technologies can impact our knowledge of bacterial diseases and their control through vaccine development. The major breakthroughs in the last couple of decades include low cost high throughput genomics, proteomics, cellular immunology and the delicate network of immune-cytokines, bioinformatics, immune-informatics, and disease modelling. Together, these newer developments can provide a real impact on our understanding of infectious diseases and their control by vaccination.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.153
GPT teacher head0.357
Teacher spread0.205 · 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