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Record W2016163629 · doi:10.1089/104454901753438561

Learning to Remember: Generation and Maintenance of T-Cell Memory

2001· review· en· W2016163629 on OpenAlexaff
Patrick Champagne, Alain R. Dumont, Rafick‐Pierre Sékaly

Bibliographic record

VenueDNA and Cell Biology · 2001
Typereview
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversité de MontréalMcGill UniversityCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsBiologyImmune systemImmunological memoryMemory cellExtracellularIntracellularHoming (biology)ImmunologyNeuroscienceCell biologyImmunityEcology

Abstract

fetched live from OpenAlex

Immunologic memory results from a carefully coordinated interplay between cells of the immune system. In this review, we explore various aspects of the nature, generation, and maintenance of T lymphocyte-mediated immunologic memory. In light of the demonstrated heterogeneity of the memory T-cell pool, we hypothesize that subsets of memory T cells instructed to mature to distinct differentiation stages may differ, not only in functional and homing properties, but also in the conditions they require for survival, including antigen persistence and cytokine environment. Hence, according to this hypothesis, distinct memory T-cell subsets result from the nature and timing of the signals provided by the immune environment and occupy distinct niches. Intracellular and extracellular molecular mechanisms that underlie and modulate T-cell memory are discussed.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.004

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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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

Citations13
Published2001
Admission routes1
Has abstractyes

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