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Relationships between floral characters, pollination mechanisms, life forms, and habitats in Araceae

2008· article· en· W2101618609 on OpenAlexafffund
Mathieu Chouteau, Marc Gibernau, Denis Barabé

Bibliographic record

VenueBotanical Journal of the Linnean Society · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyPollinationPollinatorPollenInflorescenceOvuleEvergreenAraceaeBotanyPhenologyTemperate climateAnemophilySexual reproductionEcology

Abstract

fetched live from OpenAlex

The floral traits of the inflorescences of angiosperms have coevolved to ensure and maximize pollination success. Other factors believed to influence floral architecture are external (for example, ecological) to the inflorescence. In order to understand the relationships between such factors and floral characters, 12 floral traits were measured in 54 species of Araceae. An analysis was performed to determine how these traits are linked to the following: (1) self-pollination capacity; (2) life form (evergreen versus seasonally dormant); (3) climatic conditions; and (4) type of pollinator (i.e. flies, bees, or beetles). A significant difference was found between the pollen to ovule ratio of the species able to self-pollinate and those unable to self-pollinate. Evergreen and tropical aroids produced a larger number of gametes than did seasonally dormant and temperate taxa. Finally, several floral traits, such as pollen volume and number, number of female flowers, and flower sexual type (unisexual or bisexual), showed clear differences between the three pollinator types. Variations in floral traits between the different life forms and climatic conditions are discussed with respect to pollination efficiency and properties of the growing season. The pollen to ovule ratio cannot be considered as an accurate indicator of breeding systems in aroids because of the particular pollination ecology of the family.

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)0.001
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 score0.038
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.090
GPT teacher head0.221
Teacher spread0.131 · 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

Citations35
Published2008
Admission routes2
Has abstractyes

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