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Record W4389977585 · doi:10.30901/2658-6266-2023-2-o2

Introduction and breeding of shadbush in Russia and abroad

2023· article· en· W4389977585 on OpenAlexaboutno aff
G. A. Rengarten

Bibliographic record

VenuePLANT BIOTECHNOLOGY AND BREEDING · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsOrnamental plantCropGeographyEconomic botanyAgroforestryBiologySowingHorticultureBotanyForestryPlant ecology

Abstract

fetched live from OpenAlex

Shadbush is one of the underutilized berry crops. Originally, it was an ornamental crop, but now it is increasingly used as a food crop. Numerous species of shadbush belong to the genus Amelanchier Medik.; wild species grow in North America, Europe, as well as in Western and Eastern Asia, and each region has different species composition. The year of 1590 marked the beginning of introduction of wild shadbush species with the most valuable features to other countries. In the 19th century, the introduction of shadbush became most popular. In 1800, shadbush breeding was launched in Canada, and then in the USA. In 1937, the production of commercial varieties was established. At present, in Russia, the most productive work on introduction and breeding of shadbush is carried out in Michurinsk (All-Russian Scientific Research Institute of Horticulture named after I.V. Michurin), Novosibirsk (Central Siberian Botanical Garden of SB RAS), and Moscow (N.V. Tsitsin Main Botanical Garden). Unfortunately, the assortment of shadbush varieties in Russia is still quite limited and is represented by only two varieties. In recent years, the development of methods of shadbush clonal micropropagation has been underway, which makes it possible to obtain planting material on an industrial scale and accelerate the reproduction of rare varieties.

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 score0.881
Threshold uncertainty score0.117

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 head0.016
GPT teacher head0.214
Teacher spread0.198 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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