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STRONGER CONVEX (STABILIZING) SELECTION ON HOMOLOGOUS SEXUAL DISPLAY TRAITS IN FEMALES THAN IN MALES: A MULTIPOPULATION COMPARISON IN DROSOPHILA SERRATA

2010· article· en· W2086228617 on OpenAlexaff
Howard D. Rundle, Stephen F. Chenoweth

Bibliographic record

VenueEvolution · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsOntario GenomicsUniversity of Ottawa
FundersAustralian Research CouncilUniversity of Queensland
KeywordsBiologySexual selectionMate choiceSelection (genetic algorithm)Evolutionary biologyPreferenceSex pheromoneFecundityDrosophila (subgenus)ZoologyMatingGeneticsDemographyPopulationGeneStatisticsArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

Mutual mate choice for homologous sexual display traits has been demonstrated in several recent studies yet little attention has been given to quantitative comparison of the strength and form of mate preferences between the sexes. Such comparisons may provide important insight into the evolution of mate choice for honest signals. In particular, because females generally provide the majority of resources for initial offspring development, female displays may trade-off with fecundity, causing preference evolution to differ between the sexes. Recent theory suggests that adaptive male preferences for honest displays in females are possible under certain conditions and may result in preferences that are convex (i.e., stabilizing) in form. We compared sexual selection on a suite of contact pheromones arising from mutual mate choice using nine separate geographic populations of Drosophila serrata. We show that the convex selection is stronger on females than on males overall in these populations, and that convex selection is the predominate form of nonlinear selection on females but not males.

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 score0.448
Threshold uncertainty score0.559

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 head0.057
GPT teacher head0.263
Teacher spread0.206 · 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

Citations31
Published2010
Admission routes1
Has abstractyes

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