MétaCan
Menu
Back to cohort
Record W4303832780 · doi:10.3390/jox12040020

Antiviral and Anti-Inflammatory Plant-Derived Bioactive Compounds and Their Potential Use in the Treatment of COVID-19-Related Pathologies

2022· review· en· W4303832780 on OpenAlex
Purvi Trivedi, Amna Abbas, Christine Lehmann, H.P. Vasantha Rupasinghe

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 Xenobiotics · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsMcMaster UniversityDalhousie University
Fundersnot available
KeywordsChillsMedicineCoronavirus disease 2019 (COVID-19)DiseaseCoronavirusRespiratory tractIntensive care medicineBronchiolitisSocial distanceVaccinationPandemicImmunologyRespiratory systemVirusInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

The highly contagious coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic and public health emergency as it has taken the lives of over 5.7 million in more than 180 different countries. This disease is characterized by respiratory tract symptoms, such as dry cough and shortness of breath, as well as other symptoms, including fever, chills, and fatigue. COVID-19 is also characterized by the excessive release of cytokines causing inflammatory injury to the lungs and other organs. It is advised to undergo precautionary measures, such as vaccination, social distancing, use of masks, hygiene, and a healthy diet. This review is aimed at summarizing the pathophysiology of COVID-19 and potential biologically active compounds (bioactive) found in plants and plant food. We conclude that many plant food bioactive compounds exhibit antiviral and anti-inflammatory properties and support in attenuating organ damage due to reduced cytokine release and improving the recovery process from COVID-19 infection.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.296
Teacher spread0.248 · 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