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Division of labour within flowers: heteranthery, a floral strategy to reconcile contrasting pollen fates

2009· article· en· W2014617516 on OpenAlexaff
Mario Vallejo‐Marín, Jessamyn S. Manson, James D. Thomson, Spencer C. H. Barrett

Bibliographic record

VenueJournal of Evolutionary Biology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPollenBiologyPollinatorPollinationStamenZoophilyBotanyPollen sourceDivision (mathematics)

Abstract

fetched live from OpenAlex

In many nectarless flowering plants, pollen serves as both the carrier of male gametes and as food for pollinators. This can generate an evolutionary conflict if the use of pollen as food by pollinators reduces the number of gametes available for cross-fertilization. Heteranthery, the production of two or more stamen types by individual flowers reduces this conflict by allowing different stamens to specialize in 'pollinating' and 'feeding' functions. We used experimental studies of Solanum rostratum (Solanaceae) and theoretical models to investigate this 'division of labour' hypothesis. Flight cage experiments with pollinating bumble bees (Bombus impatiens) demonstrated that although feeding anthers are preferentially manipulated by bees, pollinating anthers export more pollen to other flowers. Evolutionary stability analysis of a model of pollination by pollen consumers indicated that heteranthery evolves when bees consume more pollen than should optimally be exchanged for visitation services, particularly when pollinators adjust their visitation according to the amount of pollen collected.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.248
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations153
Published2009
Admission routes1
Has abstractyes

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