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Record W4386783033 · doi:10.3390/v15091926

Humoral Responses Elicited after a Fifth Dose of SARS-CoV-2 mRNA Bivalent Vaccine

2023· article· en· W4386783033 on OpenAlexafffund
Alexandra Tauzin, Guillaume Beaudoin-Bussières, Mehdi Benlarbi, Manon Nayrac, Yuxia Bo, Gabrielle Gendron‐Lepage, Halima Medjahed, Josée Perreault, Laurie Gokool, Pascale Arlotto, Chantal Morrisseau, Cécile Tremblay, Daniel E. Kaufmann, Valérie Martel‐Laferrière, Inès Levade, Marceline Côté, Renée Bazin, Andrés Finzi

Bibliographic record

VenueViruses · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsInstitut National de Santé Publique du QuébecUniversity of OttawaHéma-QuébecUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Foundation for InnovationCanada Research ChairsFondation du CHUM
KeywordsBivalent (engine)VirologyBiologyMessenger RNAImmunologyGeneticsChemistryGene

Abstract

fetched live from OpenAlex

While an important part of the world's population is vaccinated against SARS-CoV-2, new variants continue to emerge. We observe that even after a fifth dose of the mRNA bivalent vaccine, most vaccinated individuals have antibodies that poorly neutralize several Omicron subvariants, including BQ.1.1, XBB, XBB.1.5, FD.1.1, and CH.1.1. However, Fc-effector functions remain strong and stable over time against new variants, which may partially explain why vaccines continue to be effective. We also observe that donors who have been recently infected have stronger antibody functional activities, including neutralization and Fc-effector functions, supporting the observations that hybrid immunity leads to better humoral responses.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.119
GPT teacher head0.410
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations10
Published2023
Admission routes2
Has abstractyes

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