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Record W2597176252 · doi:10.1074/jbc.r117.777102

Contribution of type III interferons to antiviral immunity: location, location, location

2017· review· en· W2597176252 on OpenAlexaff
Sergei V. Kotenko, Joan E. Durbin

Bibliographic record

VenueJournal of Biological Chemistry · 2017
Typereview
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsInstitute of Infection and Immunity
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsImmunityInterferonVirologyBiologyComputational biologyChemistryImmunologyImmune system

Abstract

fetched live from OpenAlex

Type I interferons (IFN-α/β) and the more recently identified type III IFNs (IFN-λ) function as the first line of defense against virus infection and regulate the development of both innate and adaptive immune responses. Type III IFNs were originally identified as a novel ligand-receptor system acting in parallel with type I IFNs, but subsequent studies have provided increasing evidence for distinct roles for each IFN family. In addition to their compartmentalized antiviral actions, these two systems appear to have multiple levels of cross-regulation and act coordinately to achieve effective antimicrobial protection with minimal collateral damage to the host.

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)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.063
GPT teacher head0.349
Teacher spread0.286 · 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

Citations152
Published2017
Admission routes1
Has abstractyes

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