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The Role of Animal Pollination in Plant Speciation: Integrating Ecology, Geography, and Genetics

2009· article· en· W2106325139 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Ecology Evolution and Systematics · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGenetic algorithmPollinatorPollinationBiologyReproductive isolationEcological speciationEcologyEvolutionary biologyDiversification (marketing strategy)Genetic variationGene flowPopulationPollenSociology

Abstract

fetched live from OpenAlex

Although animal pollination is often proposed as a major driver of floral divergence, questions remain about its importance in plant speciation. One issue is whether pollinator specialization, traditionally thought necessary for floral isolation, is prevalent enough to have played a major role in speciation. Furthermore, the ecological and geographic scenarios under which pollinator transitions occur are poorly understood, and the underlying genetic factors are just beginning to be uncovered for a few systems. Nevertheless, macroevolutionary studies consistently show that transitions to animal pollination are accompanied by an increase in diversification rate. Here we consider several models and diverse empirical data on how pollinators could influence speciation. We conclude that floral isolation is rarely, if ever, sufficient to cause speciation on its own, but that it acts synergistically with other isolating mechanisms. A more comprehensive approach is the key to an improved understanding of the role of pollinators in angiosperm speciation.

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.

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 score0.109
Threshold uncertainty score0.108

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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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