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Record W4220720900 · doi:10.31665/jfb.2022.17296

Upregulation of immune system against COVID-19: The role of food science, nutrition and bioactive compounds

2022· article· en· W4220720900 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Food Bioactives · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDiverse Scientific Research Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Round tablePandemicChinSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakImmune systemMedicineSession (web analytics)Political scienceLibrary scienceMedical educationImmunologyVirologyInternal medicineBusinessDiseaseComputer scienceInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

A scientific round table was held on March 16, 2022 to discuss the role of food science, nutrition and bioactive compounds on upregulating the body's immune system against SARS-CoV-2. The panel from an international group of experts in food science, nutrition, microbiology and medicine provided the latest scientific information associated with the COVID-19 pandemic. The roundtable was organised by the Dr Chin-Kun Wang of the Academy Executive Council chaired by Dr. Aman Wrakartakusumah (Indonesia) and Charles Aworth (Nigeria). The session was concluded by a question and answer period with a summary from Dr. Roger Clemens (USA).

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.387
Teacher spread0.326 · 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