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Record W1990218988 · doi:10.1074/jbc.r700013200

Innate Immunity Minireview Series: Making Biochemical Sense of Nucleic Acid Sensors That Trigger Antiviral Innate Immunity

2007· review· en· W1990218988 on OpenAlexaboutno aff
Charles E. Samuel

Bibliographic record

VenueJournal of Biological Chemistry · 2007
Typereview
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsTRIFInterferon regulatory factorsInterferonBiologyInnate immune systemTLR7RIG-IToll-like receptorIRF3MDA5TLR3Cell biologyPattern recognition receptorReceptorVirologyRNARNA interferenceGeneBiochemistry

Abstract

fetched live from OpenAlex

An important component of the innate immune response of the host in viral infection is the production of type I interferons. Efforts to understand the molecular mechanisms by which animal viruses and also double-stranded RNA trigger the induction of interferon (IFN)2 have led to the identification of cellular sensors of viral infection. The first two minireviews in this issue provide updates on two kinds of nucleic acid sensors and the biochemical pathways by which they signal the production of interferon.

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)0.001
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0340.020

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 head0.079
GPT teacher head0.339
Teacher spread0.260 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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