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Record W4400858590 · doi:10.1016/j.ymthe.2024.07.003

Can self-amplifying RNA vaccines and viruses exchange genetic material?

2024· editorial· en· W4400858590 on OpenAlexafffund
Irafasha C Casmil, Anna K. Blakney

Bibliographic record

VenueMolecular Therapy · 2024
Typeeditorial
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsMichael Smith Health Research BCCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersCanadian Institutes of Health ResearchCanada Research ChairsMichael Smith Health Research BC
KeywordsVirologyRNABiologyGeneticsGene

Abstract

fetched live from OpenAlex

Self-amplifying RNA (saRNA) is a next-generation gene therapy vector that is adapted from an alphavirus genome and encodes therapeutic proteins and/or vaccine antigens.1 Due to their replicative capabilities, saRNA vaccines are administered at lower doses than conventionally used mRNA vaccines. saRNA can be delivered in virus-like replicon particles (VRPs) or non-viral nanoparticles, such as lipid nanoparticles (LNPs) like the recently approved ARCT-154 in Japan.2 Alphaviral-based saRNA vectors lack structural proteins but contain untranslated regions and non-structural protein sequences, thus raising concerns about recombination with other viruses in case of co-infection after 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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.324
Teacher spread0.303 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations4
Published2024
Admission routes2
Has abstractyes

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