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Record W260382763 · doi:10.14199/ppp-2012-061

Beneficial arthropods visiting Canada goldenrod (Solidago canadensis L.) in selected habitats in Wrocław area.

2012· article· en· W260382763 on OpenAlexaboutno aff
M. Hurej, Jacek Twardowski, Dominik Łukowiak, Katarzyna Wilczyńska

Bibliographic record

VenueProgress in Plant Protection · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsSolidago canadensisBiologyNectarPollinatorBeneficial insectsPopulationHabitatPollinationBotanyEcologyInvasive speciesPollenPredation

Abstract

fetched live from OpenAlex

Summary Canada goldenrod Solidago canadensis as one of the most expansive invasive plants is commonly found on the territory of Poland. Not such work has been done so far on arthropods in habitats of S. canadensis in our country. The aim of the present study was to determine the number of different groups of beneficial arthropods occurring on Canada goldenrod plants. Studies were conducted at two sites in the city of Wroclaw in 2009–2010. Three observation methods were used i.e. the direct plant monitoring, counting insects over a 1 m 2 frame and the sweep net. The obtained results show a high attractiveness of Canada goldenrod plants to the predatory, parasitic and pollinating arthropods, especially during the time of plant flowering. Among the predatory insects most frequently recorded were hoverflies (Syrphidae) and lacewings (Chrysopidae). In the sweep net catch the most numerous were spiders (Araneae) and parasitic wasps (Parasitica). A one of the species that also occurred on Canada goldenrod was the honeybee (Apis mellifera L.), especially with a high population density during late summer and early autumn, when the flowers of the other honey plants were already overblown. This indicates a high suitability of S. canadensis as a good supplementary source of nectar for pollinators.

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 score0.448
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.034
GPT teacher head0.215
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

Citations3
Published2012
Admission routes1
Has abstractyes

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