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Record W3090133106 · doi:10.3389/fimmu.2020.580641

Covid-19: Perspectives on Innate Immune Evasion

2020· review· en· W3090133106 on OpenAlexafffund
Nima Taefehshokr, Sina Taefehshokr, Nima Hemmat, Bryan Heit

Bibliographic record

VenueFrontiers in Immunology · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsRobarts Clinical TrialsWestern University
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health Research
KeywordsInnate immune systemCoronavirus disease 2019 (COVID-19)Evasion (ethics)2019-20 coronavirus outbreakVirologyImmunologyPandemicSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Immune systemMedicineBiologyInfectious disease (medical specialty)OutbreakDisease

Abstract

fetched live from OpenAlex

The ongoing outbreak of Coronavirus disease 2019 infection achieved pandemic status on March 11, 2020. As of September 8, 2020 it has caused over 890,000 mortalities world-wide. Coronaviral infections are enabled by potent immunoevasory mechanisms that target multiple aspects of innate immunity, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) able to induce a cytokine storm, impair interferon responses, and suppress antigen presentation on both MHC class I and class II. Understanding the immune responses to SARS-CoV-2 and its immunoevasion approaches will improve our understanding of pathogenesis, virus clearance, and contribute toward vaccine and immunotherepeutic design and evaluation. This review discusses the known host innate immune response and immune evasion mechanisms driving SARS-CoV-2 infection and pathophysiology.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.004

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 head0.026
GPT teacher head0.314
Teacher spread0.288 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations153
Published2020
Admission routes2
Has abstractyes

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