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Record W2077450385 · doi:10.1083/jcb.201009094

Four faces of cellular senescence

2011· review· en· W2077450385 on OpenAlexafffund
Françis Rodier, Judith Campisi

Bibliographic record

VenueThe Journal of Cell Biology · 2011
Typereview
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersInstitute of Cancer ResearchNational Cancer InstituteNational Institutes of HealthInstitut Du Cancer de MontréalCancer Research SocietyU.S. Department of Energy
KeywordsSenescenceBiologyCarcinogenesisCellular senescenceCell biologyInflammationTumor promotionCancerMechanism (biology)Cell growthCancer researchImmunologyGeneticsPhenotype

Abstract

fetched live from OpenAlex

Cellular senescence is an important mechanism for preventing the proliferation of potential cancer cells. Recently, however, it has become apparent that this process entails more than a simple cessation of cell growth. In addition to suppressing tumorigenesis, cellular senescence might also promote tissue repair and fuel inflammation associated with aging and cancer progression. Thus, cellular senescence might participate in four complex biological processes (tumor suppression, tumor promotion, aging, and tissue repair), some of which have apparently opposing effects. The challenge now is to understand the senescence response well enough to harness its benefits while suppressing its drawbacks.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0030.002

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 head0.091
GPT teacher head0.323
Teacher spread0.232 · 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

Citations1,965
Published2011
Admission routes2
Has abstractyes

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