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Record W2965681546 · doi:10.1111/1365-2656.13079

Comparing ageing and the effects of diet supplementation in wild vs. captive antler flies, <i>Protopiophila litigata</i>

2019· article· en· W2965681546 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Animal Ecology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaAustralian Research CouncilFondation Bettencourt Schueller
KeywordsAgeingBiologyMatingAntlerLongevityPopulationReproductionZoologyAnimal scienceEcologyDemography

Abstract

fetched live from OpenAlex

Few studies have simultaneously compared ageing within genetically similar populations in both laboratory and natural environments. Such comparisons are important for interpreting laboratory studies, because factors such as diet could affect ageing in environment-dependent ways. Using a natural population of antler flies (Protopiophila litigata), we conducted separate factorial experiments in 2012 and 2013 that compared age-specific male survival and mating success in laboratory cages versus a natural field environment while supplementing their diets with protein or sugar. We found consistent and substantial increases in both survival and mating rates in the laboratory compared to the field, but remarkably, despite these large differences actuarial ageing was only higher in the laboratory than in the field in 2012 and similar in the two environments in 2013. In both years, there was no difference between environments in reproductive ageing. We found that males fed protein had a higher mortality rate than males fed sugar (strong and low support in 2012 and 2013, respectively). In contrast, diet did not strongly impact average mating rates, actuarial ageing or reproductive ageing in either experiment. Our results provide the first evidence that the negative effect of protein on life span reported in many laboratory studies can also occur in wild populations, although perhaps less consistently. They also highlight how laboratory environments can influence life-history traits and suggest caution when extrapolating from the laboratory to the field.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.088

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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