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Record W2057371339 · doi:10.1086/674025

Driven Apart: The Evolution of Ploidy Differences between the Sexes under Antagonistic Selection

2013· article· en· W2057371339 on OpenAlexaff
Simone Immler, Sarah P. Otto

Bibliographic record

VenueThe American Naturalist · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPloidyBiologySelection (genetic algorithm)Context (archaeology)ReproductionEvolutionary biologyInheritance (genetic algorithm)GeneticsZoologyGene

Abstract

fetched live from OpenAlex

Sexual reproduction in eukaryotes implies a biphasic life cycle with alternating haploid and diploid phases. The nature of the biphasic life cycle varies markedly across taxa, and often either the diploid or the haploid phase is predominant. Why some taxa spend a major part of their life cycle as diploids and others as haploids remains a conundrum. Furthermore, ploidy levels may not only vary across life cycle phases but may also differ between males and females. The existence of two life cycle phases and two sexes bears a high potential for antagonistic selection, which in turn may influence the evolution of ploidy levels. We explored the evolution of ploidy levels when selection depends on both ploidy and sex. Our analyses show that antagonistic selection may drive the ploidy levels between males and females apart. In a subsequent step, we explicitly explored the evolution of arrhenotoky (i.e., haploid males and diploid females) in the context of antagonistic selection. Our model shows that selection on arrhenotoky depends on male fitness but evolves regardless of the fitness consequences to females. Overall we provide a plausible explanation for the evolution of sex differences in ploidy levels, a principle that can be extended to any system with asymmetric inheritance.

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 score0.268
Threshold uncertainty score0.992

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 studies0.0010.001
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 head0.028
GPT teacher head0.221
Teacher spread0.194 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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