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MATING DENSITY AND THE STRENGTH OF SEXUAL SELECTION AGAINST DELETERIOUS ALLELES IN<i>DROSOPHILA MELANOGASTER</i>

2008· article· en· W2040884900 on OpenAlexaff
Nathaniel P. Sharp, Aneil F. Agrawal

Bibliographic record

VenueEvolution · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologySexual selectionDrosophila melanogasterSelection (genetic algorithm)AlleleFecundityGeneticsMatingEvolutionary biologyPopulationSexual conflictGeneDemography

Abstract

fetched live from OpenAlex

Deleterious alleles constantly enter populations via mutation. Their presence reduces mean fitness and may threaten population persistence. It has been suggested that sexual selection may be an efficient way by which deleterious alleles are removed from populations but there is little direct experimental evidence. Because of its potential role in mutational meltdowns, there is particular interest in whether the strength of sexual selection changes with density. For each of eight visible markers in Drosophila melanogaster we have compared the strength of sexual selection at two densities. We find evidence of strong sexual selection against most but not all of these alleles. There is no evidence that sexual selection tends to be stronger (or weaker) at high density relative to low density. In addition, we also measure the effects of these mutations on two key parameters relevant to population productivity--juvenile viability and female fecundity. In most cases, sexual selection is as strong or stronger than these other forms of selection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.208
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations91
Published2008
Admission routes1
Has abstractyes

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