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Record W2157827336 · doi:10.3732/ajb.0800102

Pollination ecology of the high latitude, dioecious cloudberry (<i>Rubus chamaemorus</i>; Rosaceae)

2009· article· en· W2157827336 on OpenAlexafffund
Adam O. Brown, Jeremy N. McNeil

Bibliographic record

VenueAmerican Journal of Botany · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsWestern UniversityUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Louisville
KeywordsRosaceaeBiologyPollinationEcologyRubusBotanyEricaceaePollen

Abstract

fetched live from OpenAlex

In a 3-yr study, we examined the pollinator guild and intersexual floral characteristics of the dioecious, perennial cloudberry (Rubus chamaemorus), which flowers in early spring. The findings contribute to our general understanding of pollination ecology at high latitudes and provide important information for the commercialization of cloudberry. Female flowers were smaller than males but provided more nectar, although this resource was low in both sexes. Insects from 43 families visited cloudberry flowers, yet four families (Apidae, Halictidae, Muscidae, Syrphidae) represented ca. 87% of all visitors observed. Introduction experiments revealed that apids and muscids are significantly poorer pollinators (based on fruit production) than halictids and syrphids, but when fruit mass or seed set was considered, there were no significant differences between families. Pollinator importance, a product of flower visitation frequency and seed set effectiveness, revealed that the dipterans were of paramount importance to the pollination of cloudberry. Furthermore, they are limited to cloudberry because their lapping mouthparts exclude them from accessing the nutritional rewards of competing Ericaceae flowers. While the total number of pollinator families observed suggest a generalist pollination system, if one considers the dominant pollinators (flies) as a functional group, then this insect-flower relationship could be considered a specialized one.

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)0.000
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 score0.833
Threshold uncertainty score0.119

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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

Citations40
Published2009
Admission routes2
Has abstractyes

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