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Does the human immune system ever really become “senescent”?

2017· preprint· en· W2744846584 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueF1000Research · 2017
Typepreprint
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsHealth Sciences North
FundersBundesministerium für Bildung und ForschungDeutsche ForschungsgemeinschaftEuropean Commission
KeywordsImmunosenescenceImmune systemContext (archaeology)DiseaseImmunologyAgeingBiologyAutoimmunityMedicineGeneticsPathology

Abstract

fetched live from OpenAlex

Like all somatic tissues, the human immune system changes with age. This is believed to result in an increased frequency of, and susceptibility to, infectious disease and to contribute to a wide range of non-communicable age-associated diseases in later life, especially cancer, cardiovascular disease, and autoimmunity. The majority of studies addressing immune ageing has been cross-sectional, but limited longitudinal studies are contributing to a better understanding of age-associated changes, as opposed to differences, and their clinical relevance. However, intriguing differences are emerging that implicate highly context-dependent immune ageing processes, mitigating against current generalisations concerning human immunosenescence and indicating the necessity for detailed comparisons of different populations, even those that would appear quite similar at first glance.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0030.006
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0020.002

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 head0.072
GPT teacher head0.399
Teacher spread0.327 · 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