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Record W4200484666 · doi:10.3390/vaccines9121490

Vaccine Technologies and Platforms for Infectious Diseases: Current Progress, Challenges, and Opportunities

2021· review· en· W4200484666 on OpenAlexafffund
Majed Ghattas, Garima Dwivedi, Marc Lavertu, Mohamad‐Gabriel Alameh

Bibliographic record

VenueVaccines · 2021
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDNA vaccinationGlycoconjugateConjugate vaccineVaccinationBiologyVirologyComputational biologyBiotechnologyAntigenImmunizationImmunologyBioinformatics

Abstract

fetched live from OpenAlex

Vaccination is a key component of public health policy with demonstrated cost-effective benefits in protecting both human and animal populations. Vaccines can be manufactured under multiple forms including, inactivated (killed), toxoid, live attenuated, Virus-like Particles, synthetic peptide, polysaccharide, polysaccharide conjugate (glycoconjugate), viral vectored (vector-based), nucleic acids (DNA and mRNA) and bacterial vector/synthetic antigen presenting cells. Several processes are used in the manufacturing of vaccines and recent developments in medical/biomedical engineering, biology, immunology, and vaccinology have led to the emergence of innovative nucleic acid vaccines, a novel category added to conventional and subunit vaccines. In this review, we have summarized recent advances in vaccine technologies and platforms focusing on their mechanisms of action, advantages, and possible drawbacks.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.164
GPT teacher head0.410
Teacher spread0.246 · 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

Citations228
Published2021
Admission routes2
Has abstractyes

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