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Record W2161333934 · doi:10.1163/15707563-00002409

Does innate immune function decline with age in captive ruffs Philomachus pugnax?

2012· article· en· W2161333934 on OpenAlexafffund
Silke Nebel, Deborah M. Buehler, Shawn P. Kubli, David B. Lank, Christopher G. Guglielmo

Bibliographic record

VenueAnimal Biology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsSimon Fraser UniversityRoyal Ontario MuseumUniversity of TorontoWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsImmunosenescenceInnate immune systemImmune systemImmunityBiologyImmunologyTraitDemography

Abstract

fetched live from OpenAlex

Immunosenescence, the decline of immune function with age, results in increased risk of infection as an individual ages. The underlying reasons are still poorly understood. Here, we ask whether the rate of decline of an immune indicator is positively correlated with the cost of maintaining it, as predicted by optimal resource allocation theory. Using 30 female ruffs Philomachus pugnax ranging in age from 0.5-12 years we found no effect of age on five indicators of constitutive innate immunity, which is cheap to use and maintain. Body temperature increase following injection with lipopolysaccharide is an indicator of induced innate immunity, which is energetically expensive, and showed a curvilinear relationship with age, with a maximum in middle-aged birds. Our results suggest that changes in immune function with age may depend on the energetic cost of using an immune trait.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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)0.0010.000

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 head0.243
Teacher spread0.222 · 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

Citations8
Published2012
Admission routes2
Has abstractyes

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