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From rare disorders of immunity to common determinants of infection: Following the mechanistic thread

2022· review· en· 145 citations· W4292240525 on OpenAlex· 10.1016/j.cell.2022.07.004

Why is this work in the frame?

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

Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Not applicableConsensus signal: none
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.995
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.027
GPT teacher head0.292
Teacher spread
0.264 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

The immense interindividual clinical variability during any infection is a long-standing enigma. Inborn errors of IFN-γ and IFN-α/β immunity underlying rare infections with weakly virulent mycobacteria and seasonal influenza virus have inspired studies of two common infections: tuberculosis and COVID-19. A TYK2 genotype impairing IFN-γ production accounts for about 1% of tuberculosis cases, and autoantibodies neutralizing IFN-α/β account for about 15% of critical COVID-19 cases. The discovery of inborn errors and mechanisms underlying rare infections drove the identification of common monogenic or autoimmune determinants of related common infections. This "rare-to-common" genetic and mechanistic approach to infectious diseases may be of heuristic value.

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.

The record

Venue
Cell
Topic
Immunodeficiency and Autoimmune Disorders
Field
Immunology and Microbiology
Canadian institutions
not available
Funders
Horizon 2020 Framework ProgrammeUniversité de LausanneInstitut National de la Santé et de la Recherche MédicaleFondation du SouffleRockefeller UniversityFondation pour la Recherche MédicaleMcGill UniversityGlenn Foundation for Medical ResearchSCOR Corporate Foundation for ScienceÉcole Polytechnique Fédérale de LausanneUK Research and InnovationNational Institutes of HealthFisher Center for Alzheimer's Research FoundationNational Institute of Neurological Disorders and StrokeMeyer FoundationSt. Giles FoundationNational Center for Advancing Translational SciencesUniversité Paris-SaclayAgence Nationale de la RechercheNational Institute of Allergy and Infectious DiseasesHoward Hughes Medical Institute
Keywords
BiologyImmunologyImmunityTuberculosisRubellaVirologyImmune systemMeaslesVaccinationMedicine
Has abstract in OpenAlex
yes