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Record W2150875539 · doi:10.4039/n07-060

Flower-visiting and mating behaviour of <i>Eulonchus sapphirinus</i> (Diptera: Acroceridae)

2008· article· en· W2150875539 on OpenAlexaff
Christopher J. Borkent, Evert I. Schlinger

Bibliographic record

VenueThe Canadian Entomologist · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsNectarPollinatorBiologyPollinationMatingInsectForagingPollenEcologyZoologyBotany

Abstract

fetched live from OpenAlex

Abstract Acrocerid flies are often considered to be rare and their role in pollination is poorly understood. In this study, adult Eulonchus sapphirinus Osten Sacken were common on flowers of Geranium robertianum L. (Geraniaceae) in Olympic National Park, Washington, and have morphological and behavioural characteristics that indicate a dependence on floral nectar. Both males and females of this species are good potential pollinators from a behavioural standpoint. They make few revisits to individual flowers, remain highly constant to one flowering species in each nectar-foraging bout, and carry pollen on their bodies. Individuals were abundant and formed the majority of insect visitors to G. robertianum flowers. Males and females differed in their flower-visiting behaviour, with females visiting more individual flowers and doing so more slowly than males. This difference between the sexes appears to relate to mating behaviour, which takes place within the flower patches. The ramifications of the observed flower-visiting and mating behaviour for flower pollination are discussed. This study shows that based on both their abundance and their behaviour, these flies are potentially important pollinators in certain habitats.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.044
GPT teacher head0.202
Teacher spread0.158 · 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

Citations13
Published2008
Admission routes1
Has abstractyes

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