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Record W2962930060 · doi:10.1111/nph.16075

Reproductive transitions in plants and animals: selfing syndrome, sexual selection and speciation

2019· review· en· W2962930060 on OpenAlexafffund
Asher D. Cutter

Bibliographic record

VenueNew Phytologist · 2019
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSelfingBiologyInbreeding depressionEvolutionary biologyReproductive isolationSexual selectionOutcrossingGenetic algorithmGeneticsInbreedingEcologyPopulation

Abstract

fetched live from OpenAlex

The evolution of predominant self-fertilisation frequently coincides with the evolution of a collection of phenotypes that comprise the 'selfing syndrome', in both plants and animals. Genomic features also display a selfing syndrome. Selfing syndrome traits often involve changes to male and female reproductive characters that were subject to sexual selection and sexual conflict in the obligatorily outcrossing ancestor, including the gametic phase for both plants and animals. Rapid evolution of reproductive traits, due to both relaxed selection and directional selection under the new status of predominant selfing, lays the genetic groundwork for reproductive isolation. Consequently, shifts in sexual selection pressures coupled to transitions to selfing provide a powerful paradigm for investigating the speciation process. Plant and animal studies, however, emphasise distinct selective forces influencing reproductive-mode transitions: genetic transmission advantage to selfing or reproductive assurance outweighing the costs of inbreeding depression vs the costs of males and meiosis. Here, I synthesise links between sexual selection, evolution of selfing and speciation, with particular focus on identifying commonalities and differences between plant and animal systems and pointing to areas warranting further synergy.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.121
GPT teacher head0.289
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 designOther design
Domainnot available
GenreReview

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

Citations134
Published2019
Admission routes2
Has abstractyes

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