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Record W4403225357 · doi:10.1016/j.devcel.2024.09.011

Sex-biased human thymic architecture guides T cell development through spatially defined niches

2024· article· en· W4403225357 on OpenAlexafffund
Laura N Stankiewicz, Kevin Salim, Emily A Flaschner, Yu Xin Wang, John M. Edgar, Lauren J. Durland, Bruce Z B Lin, Grace C. Bingham, Matthew C. Major, Ross D. Jones, Helen M. Blau, Elizabeth J. Rideout, Megan K. Levings, Peter W. Zandstra, Fábio Rossi

Bibliographic record

VenueDevelopmental Cell · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of British Columbia HospitalBC Children's HospitalUniversity of British Columbia
FundersNational Institute of Neurological Disorders and StrokeWellcome LeapBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthNational Institute on AgingGenome British ColumbiaBC Children's HospitalMichael Smith Health Research BCUniversities Space Research AssociationWellcome TrustCanadian Institutes of Health ResearchLi Ka Shing Foundation
KeywordsBiologyNicheEcological nicheEvolutionary biologyEcology

Abstract

fetched live from OpenAlex

fibroblasts, and characterize the medullary niches surrounding Hassall's corpuscles. Together, these data represent an age-matched spatial multiomic resource to investigate how sex-based differences in thymus regulation and T cell development arise, providing an essential resource to understand the mechanisms underlying immune function and dysfunction in males and females.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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

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 head0.017
GPT teacher head0.227
Teacher spread0.210 · 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 designObservational
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

Citations21
Published2024
Admission routes2
Has abstractyes

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