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Potential role of immunosenescence in cancer development

2010· review· en· W1616315157 on OpenAlexaff
Tamàs Fülöp, Rami Kotb, Carl Fortin, Graham Pawelec, Flávia De Angelis, Anis Larbi

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2010
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsImmunosenescenceImmunosurveillanceImmune systemCarcinogenesisCancerImmunologyMechanism (biology)BiologyMedicineGenetics

Abstract

fetched live from OpenAlex

The incidence and prevalence of most cancers increase with age. The reasons for this may include tumor escape mechanisms and decreased immunosurveillance, but most are caused by the time required for carcinogenesis, according to most scientists. The immune system is a unique mechanism of defense against pathogens and possibly cancers; however, there is a body of evidence that the immune system of the aged is eroded, a phenomenon termed immunosenescence. There is a growing interest in immunosenescence and how it may contribute to the increased number of cancers with aging. Each arm of the immune system, innate and adaptive, is altered with aging, contributing to increased tumorigenesis. Understanding the contribution of immunosenescence to cancer development and progression may lead to better interventions for the elderly.

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)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
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 head0.078
GPT teacher head0.364
Teacher spread0.286 · 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

Citations160
Published2010
Admission routes1
Has abstractyes

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