MétaCan
Menu
Back to cohort
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 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)0.007
metaresearch head score (Gemma)0.016
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.015
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0040.007
Open science0.0020.001
Research integrity0.0150.021
Insufficient payload (model declined to judge)0.0050.005

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 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
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

Explore more

Same venueMolecular TherapySame topicViral gastroenteritis research and epidemiologyFrench-language works237,207