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Record W4414532962 · doi:10.1098/rsos.251127

Testing adaptive hypotheses for an evolutionarily conserved trait through slow-motion videos of pollinators

2025· article· en· W4414532962 on OpenAlexaff
Robin Waterman, Jeffrey K. Conner

Bibliographic record

VenueRoyal Society Open Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsKellogg's (Canada)
FundersDivision of Environmental BiologyDivision of Biological InfrastructureNational Institute of Food and Agriculture
KeywordsPollinatorTraitStamenAdaptation (eye)PollinationKey (lock)

Abstract

fetched live from OpenAlex

Traits conserved across evolutionary time often provide compelling examples of key adaptations for a given taxonomic group. Tetradynamy is the presence of four long stamens plus two short stamens within a flower and is conserved across most of the roughly 4000 species in the mustard family, Brassicaceae. While this differentiation in stamens is hypothesized to play a role in pollination efficiency, very little is known about the potential function of the two stamen types. The present study sheds new light on this mystery using wild radish ( Raphanus raphanistrum ), a widespread and well-studied tetradynamous plant. We used data collected from slow-motion videos of pollinators visiting wild radish flowers to test three adaptive hypotheses (not mutually exclusive): (H1) short and long stamens are specialized for either feeding or pollinating; (H2) short and long stamens are specialized for different pollinator taxa; and (H3) the presence of short and long stamens increases pollinator movement and thus effectiveness. We find evidence consistent with hypothesis H3, but no evidence for hypotheses H1 or H2. Thus, tetradynamy may be an adaptation for generalized pollination, enabling effective visits by the variety of pollinators visiting most species of Brassicaceae.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.129
GPT teacher head0.295
Teacher spread0.166 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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