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Record W2151128505 · doi:10.1111/nph.13696

Dioecy does not consistently accelerate or slow lineage diversification across multiple genera of angiosperms

2015· article· en· W2151128505 on OpenAlexafffund
Niv Sabath, Emma E. Goldberg, Lior Glick, Moshe Einhorn, Tia‐Lynn Ashman, Ray Ming, Sarah P. Otto, Jana C. Vamosi, Itay Mayrose

Bibliographic record

VenueNew Phytologist · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaIsrael Science FoundationUnited States - Israel Binational Science FoundationUnited States-Israel Binational Science FoundationNational Science Foundation
KeywordsDioecyBiologyLineage (genetic)Diversification (marketing strategy)Evolutionary biologyTraitEcologyGeneticsGene

Abstract

fetched live from OpenAlex

Dioecy, the sexual system in which male and female organs are found in separate individuals, allows greater specialization for sex-specific functions and can be advantageous under various ecological and environmental conditions. However, dioecy is rare among flowering plants. Previous studies identified contradictory trends regarding the relative diversification rates of dioecious lineages vs their nondioecious counterparts, depending on the methods and data used. We gathered detailed species-level data for dozens of genera that contain both dioecious and nondioecious species. We then applied a probabilistic approach that accounts for differential speciation, extinction, and transition rates between states to examine whether there is an association between dioecy and lineage diversification. We found a bimodal distribution, whereby dioecious lineages exhibited higher diversification in certain genera but lower diversification in others. Additional analyses did not uncover an ecological or life history trait that could explain a context-dependent effect of dioecy on diversification. Furthermore, in-depth simulations of neutral characters demonstrated that such bimodality is also found when simulating neutral characters across the observed trees. Our analyses suggest that - at least for these genera with the currently available data - dioecy neither consistently places a strong brake on diversification nor is a strong driver.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.388

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 head0.168
GPT teacher head0.280
Teacher spread0.112 · 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

Citations46
Published2015
Admission routes2
Has abstractyes

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