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Record W6892111181 · doi:10.5061/dryad.hdr7sqvgn

The evolution of age-specific choosiness when mating

2020· dataset· en· W6892111181 on OpenAlexaff

Bibliographic record

VenueDRYAD · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsQueen's University
Fundersnot available
KeywordsSelection (genetic algorithm)Mate choiceGenetic FitnessBiological evolutionLife historySexual selectionReproduction

Abstract

fetched live from OpenAlex

Mate choice is a crucial element of many processes in evolutionary biology. Empirical research has shown that mating preference and choosiness often change with age. Understanding the evolutionary causes of patterns of age-specific choosiness is challenging because different mechanisms can give rise to the same pattern. Instead of focusing on the optimal age-specific choosiness strategy given fitness trade-offs, we approach this question from a more general standpoint and ask how the strength of selection on choosiness changes with the age at which it is expressed. We show that the strength of selection on a modifier of choosiness at a given age depends on the relative contribution of this age class to the pool of offspring but does not depend directly on the strength of selection on fitness components at the age affected by the modifier. We illustrate our results by contrasting two life histories from the literature. We further show how mutation-selection balance at the choosiness locus can shape age-specific choosiness. Our results provide new insights for understanding the evolution of choosiness throughout life, with implications for understanding the evolution of mate choice and reproductive isolation.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.015
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.015

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 head0.254
Teacher spread0.226 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2020
Admission routes1
Has abstractyes

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