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Record W4381250869 · doi:10.1016/j.vaccine.2023.06.051

Assessing the stability-indicating properties of alternative potency assays for inactivated influenza vaccine

2023· article· en· W4381250869 on OpenAlexaff
AA Ekimov, Balasubramanian Arunachalam, Taylor Blake, Jesse Bodle, Laura Couzens, Sitara Dubey, Maryna C. Eichelberger, Othmar G. Engelhardt, Francesco Gubinelli, Manju B. Joshi, Darya Melnyk, Giuseppe Palladino, Peter Rigsby, Steven Rockman, N. N. Savina, Elena Smith, Shawn Gilchrist

Bibliographic record

VenueVaccine · 2023
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsEXP (Canada)
Fundersnot available
KeywordsPotencyImmunogenicityRadial immunodiffusionInfluenza vaccineAntigenVirologyMicrobiologyImmunologyBiologyVaccinationAntibodyBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Determination of the potency of a vaccine is critical to ensuring that an appropriate dose is delivered, lot-to-lot consistency is maintained, and that the formulation is stable over the life of the vaccine. The potency of inactivated influenza vaccines is determined routinely by the Single Radial Immunodiffusion (SRID) assay. A number of alternative potency assays have been proposed and have been under evaluation in recent years. The aim of this study was to compare a surface plasmon resonance-based assay and two different enzyme linked immunoassays against the current potency assay, SRID, and against mouse immunogenicity when haemagglutinin antigen of the A(H1N1)pdm09 component of an inactivated influenza vaccine is stressed by elevated temperature, low pH and freezing. This analysis demonstrated that the alternative assays had good correspondence with SRID for samples from most stress conditions and that the immunogenicity in mice corresponded with potency in SRID for all stress samples. Subject to further analysis, the assays have been shown to have the potential to possibly replace, and at least complement, SRID.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.195
GPT teacher head0.425
Teacher spread0.230 · 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 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

Citations9
Published2023
Admission routes1
Has abstractyes

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