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Record W3216605774 · doi:10.1016/j.celrep.2021.110071

Heterogeneity of human anti-viral immunity shaped by virus, tissue, age, and sex

2021· article· en· W3216605774 on OpenAlexfundno aff
Maya M.L. Poon, Eve Byington, Wenzhao Meng, Masaru Kubota, Rei Matsumoto, Alba Grifoni, Daniela Weiskopf, Pranay Dogra, Nora Lam, Peter A. Szabo, Basak B. Ural, Steven B. Wells, Aaron M. Rosenfeld, Maigan Brusko, Todd M. Brusko, Thomas J. Connors, Alessandro Sette, Peter A. Sims, Eline T. Luning Prak, Yufeng Shen, Donna L. Färber

Bibliographic record

VenueCell Reports · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood InstituteNational Cancer InstituteNational Science FoundationNational Institutes of HealthCanadian Institutes of Health ResearchLeona M. and Harry B. Helmsley Charitable TrustAmerican Autoimmune Related Diseases AssociationNational Center for Research ResourcesCancer Research Institute
KeywordsBiologyImmune systemImmunityVirusImmunologyVirologyCD8

Abstract

fetched live from OpenAlex

T cells recognizing the ubiquitous pathogens influenza and cytomegalovirus. Our results reveal that virus specificity determines overall magnitude, tissue distribution, differentiation, and clonal repertoire of virus-specific T cells. Age and sex influence T cell differentiation and dissemination in tissues, while T cell tissue residence and functionality are highly correlated with the site. Together, our results demonstrate how the covariates of virus, tissue, age, and sex impact the anti-viral immune response, which is important for targeting, monitoring, and predicting immune responses to existing and emerging viruses.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations61
Published2021
Admission routes1
Has abstractyes

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