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Record W2138344944 · doi:10.1098/rsbl.2009.0335

Body condition but not dietary restriction prolongs lifespan in a semelparous capital breeder

2009· article· en· W2138344944 on OpenAlexafffund
Michael M. Kasumovic, Robert C. Brooks, Maydianne C. B. Andrade

Bibliographic record

VenueBiology Letters · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsLongevityBiologySemelparity and iteroparityContext (archaeology)CourtshipCompetition (biology)Life history theoryReproductionEcologyZoologyLife history

Abstract

fetched live from OpenAlex

Effects of diet on longevity are complex because acquired resources are shared among growth, reproduction and somatic maintenance. We simplify these axes by examining how dietary restriction and competitive contexts affect longevity using semelparous males of the Australian redback spider (Latrodectus hasselti). Plastic development of L. hasselti males results in trade-offs of body condition against faster development if females are present, facilitating scramble competition. In the absence of females, males develop slowly as high body condition adults, and are better equipped for mate searching. Here we focus on effects of diet and competitive context on body condition and longevity. Although male survival depended on body condition and exercise, contrary to studies in a wide range of taxa, dietary restriction did not increase longevity. However, there was an interactive effect of diet and competitive context on lifespan, because high-diet males reared in the absence of females lived longer than males reared in the presence of females. Thus males near females pay a survival cost of developing rapidly. This shows that life-history trade-offs affected by competitive context can impose longevity costs independent of the direct energy expenditure of searching, courtship, competition or reproduction.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.239
Teacher spread0.220 · 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 teacher head, 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

Citations33
Published2009
Admission routes2
Has abstractyes

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