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Record W4372346993 · doi:10.26786/1920-7603(2023)740

Floral scent and pollination of the invasive plant Coreopsis lanceolata in Japan

2023· article· en· W4372346993 on OpenAlexvenueno aff
Muhammad Arifin, Tomoko Okamoto

Bibliographic record

VenueJournal of Pollination Ecology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and Technology
KeywordsPollinatorPollinationBiologyBotanyPollenOvuleRange (aeronautics)Reproductive successEcologyPopulation

Abstract

fetched live from OpenAlex

The invasive plant Coreopsis lanceolata threatens ecosystems in Japan by competing for resources with native plants. This species is self-incompatible and requires pollinator agents for seed production; however, it is known to produce many seeds. Here, we document the pollination biology and plant-pollinator interactions that facilitate seed production of C. lanceolata in the introduced range. Results revealed that C. lanceolata attracted a wide array of floral visitors comprising 60 species from 20 families. Although most floral visitors could be potential pollinators, the functional groups of halictid bees appeared to be the most important pollinators of C. lanceolata in terms of visitation frequency and the ability to carry pollen. The floral scent emission of C. lanceolata consists predominantly of monoterpenes, sesquiterpenes, and benzenoids. Furthermore, the mean seed set was nearly 30% of the ovule mean. Our study confirmed that in the introduced range in Japan, C. lanceolata is integrated into the local pollinator community, especially with the functional group of halictid bees involved in the reproductive success.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.420

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 head0.043
GPT teacher head0.222
Teacher spread0.180 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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