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Record W2805749946 · doi:10.1111/1365-2435.13128

Wild and laboratory exposure to cues of predation risk increases relative brain mass in male guppies

2018· article· en· W2805749946 on OpenAlexafffund
Adam R. Reddon, Laura Chouinard‐Thuly, Ioannis Leris, Simon M. Reader

Bibliographic record

VenueFunctional Ecology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsGuppyPredationPoeciliaBiologyPoeciliidaePredatorZoologyEcologyPopulationBrain sizeFish <Actinopterygii>DemographyFishery

Abstract

fetched live from OpenAlex

Abstract There is considerable diversity in brain size within and among species, and substantial dispute over the causes, consequences and importance of this variation. Comparative and developmental studies are essential in addressing this controversy. Predation pressure has been proposed as a major force shaping brain, behaviour and life history. The Trinidadian guppy, Poecilia reticulata, shows dramatic variation in predation pressure across populations. We compared the brain mass of guppies from high and low predation populations collected in the wild. Male but not female guppies exposed to high predation possessed heavier brains for their body size compared to fish from low predation populations. The brain is a plastic organ, so it is possible that the population differences we observed were partly due to developmental responses rather than evolved differences. In a follow‐up study, we raised guppies under cues of predation risk or in a control condition. Male guppies exposed to predator cues early in life had heavier brains relative to their body size than control males, while females showed no significant effect of treatment. Collectively our results suggest that male guppies exposed to predation invest more in neural tissue, and that these differences are at least partly driven by plastic responses. A plain language summary is available for this article.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.717

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)0.0010.000

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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

Citations40
Published2018
Admission routes2
Has abstractyes

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