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Environment-dependent intralocus sexual conflict in a dioecious plant

2011· article· en· W2152120802 on OpenAlexfundno aff
Lynda F. Delph, Jonathan Andicoechea, Janet C. Steven, Christopher R. Herlihy, Samuel V. Scarpino, Daniela L. Bell

Bibliographic record

VenueNew Phytologist · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsBiologyTraitSexual dimorphismSelection (genetic algorithm)Sexual selectionNatural selectionEvolutionary biologyDioecyEcologyZoology

Abstract

fetched live from OpenAlex

Intralocus sexual conflict is a form of conflict that does not involve direct interactions between males and females. It arises when selection on a shared trait with a common genetic basis differs between the sexes. Environmental factors, such as resource availability, may influence the expression and evolutionary outcome of such conflict. We quantified the genetic variance-covariance matrix, G, for both sexes of Silene latifolia for floral and leaf traits, as well as the between-sex matrix, B. We also quantified selection on the sexes via survival for 2 yr in four natural populations that varied in water availability. Environment-dependent intralocus sexual conflict exists for specific leaf area, a trait that is genetically correlated between the sexes. Males experienced significant negative selection, but only in populations with relatively limited water availability. Females experienced weakly positive or significant stabilizing selection on the same trait. Specific leaf area is genetically correlated with flower size and number, which are sexually dimorphic in this species. The extent of intralocus sexual conflict varied with the environment. Resolution of such conflict is likely to be confounded, given that specific leaf area is highly genetically integrated with other traits that are also divergent between the sexes.

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 score0.280
Threshold uncertainty score0.704

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 head0.091
GPT teacher head0.214
Teacher spread0.122 · 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

Citations76
Published2011
Admission routes1
Has abstractyes

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