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Trait correlates and functional significance of heteranthery in flowering plants

2010· article· en· W2141363602 on OpenAlexafffund
Mario Vallejo‐Marín, Elizabeth M. Da Silva, Risa D. Sargent, Spencer C. H. Barrett

Bibliographic record

VenueNew Phytologist · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of TorontoUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Stirling
KeywordsTraitBiologyBotanyEcologyComputer science

Abstract

fetched live from OpenAlex

• Flowering plants display extraordinary diversity in the morphology of male sexual organs, yet the functional significance of this variation is not well understood. Here, we conducted a comparative analysis of floral correlates of heteranthery - the morphological and functional differentiation of anthers within flowers - among angiosperm families to identify traits associated with this condition. • We performed a phylogenetic analysis of correlated evolution between heteranthery and several floral traits commonly reported from heterantherous taxa. In addition, we quantified the effect of phylogenetic uncertainty in the observed patterns of correlated evolution by comparing trees in which polytomous branches were randomly resolved. • Heteranthery is reported from 12 angiosperm orders and is phylogenetically associated with the absence of floral nectaries, buzz-pollination and enantiostyly (mirror-image flowers). These associations are robust to particularities of the underlying phylogenetic hypothesis. • Heteranthery has probably evolved as a result of pollinator-mediated selection and appears to function to reduce the conflict of relying on pollen both as food to attract pollinators and as the agent of male gamete transfer. The relative scarcity of heteranthery among angiosperm families suggests that the conditions permitting its evolution are not easily met despite the abundance of pollen-collecting bees and nectarless flowers.

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 score0.771
Threshold uncertainty score0.703

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 head0.039
GPT teacher head0.213
Teacher spread0.174 · 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

Citations136
Published2010
Admission routes2
Has abstractyes

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