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Record W4400148102 · doi:10.1016/j.cdnut.2024.103674

Yeast-Derived Beta-Glucan Supplementation on Antibody Response Following Influenza Vaccination: A Protocol for a Randomized, Placebo-Controlled Study (M-Unity)

2024· article· en· W4400148102 on OpenAlexaff
Melissa Moreno, Kaylan B Hebert, Camilo A Vivas, Carmelo Nieves, Daniela Rivero‐Mendoza, Thomas A. Tompkins, Wendy J. Dahl

Bibliographic record

VenueCurrent Developments in Nutrition · 2024
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsLallemand (Canada)
Fundersnot available
KeywordsPlaceboAntibody responseMedicineVaccinationRandomized controlled trialAntibodyBeta-glucanProtocol (science)GlucanYeastImmunologyVirologyInternal medicineBiologyBiochemistryPathology

Abstract

fetched live from OpenAlex

Objectives: Yeast beta-glucans have shown immune-modulating effects by enhancing innate and adaptive immune responses through cytokine release and antibody production, among other immunomodulating effects. This study aims to determine the effect of yeast-derived beta-glucan supplementation on antibody titer response to influenza vaccination. Secondary outcomes include cytokine profile, incidence of fever, cold and flu symptoms, and self-perceived fatigue.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0200.004

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 head0.042
GPT teacher head0.414
Teacher spread0.371 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations0
Published2024
Admission routes1
Has abstractyes

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