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Record W1951800185 · doi:10.1111/evo.12680

Evolution of sexual dimorphism in phenotypic covariance structure in<i>Phymata</i>

2015· article· en· W1951800185 on OpenAlexaff
David Punzalan, Locke Rowe

Bibliographic record

VenueEvolution · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of TorontoRoyal Ontario Museum
FundersAmerican Museum of Natural History
KeywordsSexual dimorphismBiologyTraitEvolutionary biologyGenetic architectureSexual selectionCovarianceDivergence (linguistics)PhenotypeZoologyGeneticsStatisticsGene

Abstract

fetched live from OpenAlex

Sexual dimorphism is a consequence of both sex-specific selection and potential constraints imposed by a shared genetic architecture underlying sexually homologous traits. However, genetic architecture is expected to evolve to mitigate these constraints, allowing the sexes to approach their respective optimal mean phenotype. In addition, sex-specific selection is expected to generate sexual dimorphism of trait covariance structure (e.g., the phenotypic covariance matrix, P), but previous empirical work has not fully addressed this prediction. We compared patterns of phenotypic divergence, for three traits in seven taxa in the insect genus Phymata (Reduviidae), to ask whether sexual dimorphism in P is common and whether its magnitude relates to the extent of sexual dimorphism in trait means. We found that sexual dimorphism in both mean and covariance structure was pervasive but also that the multivariate distance between sex-specific means was correlated with sex differences in the leading eigenvector of P, while accounting for uncertainty in phylogenetic relationships. Collectively, our findings suggest that sexual dimorphism in covariance structure may be a common but underappreciated feature of dioecious populations.

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 score0.491
Threshold uncertainty score0.995

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 head0.037
GPT teacher head0.205
Teacher spread0.168 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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