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Record W6893571272 · doi:10.5281/zenodo.2283448

Cultivars of roses of Canadian breeding in collection of M.M. Gryshko National Botanical Garden of the NAS of Ukraine

2017· article· en· W6893571272 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPowdery Mildew Fungal Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarHardiness (plants)Botanical gardenGenetic resourcesHabit

Abstract

fetched live from OpenAlex

The history of rose breeding in Canada is represented. The collection of roses fund of the M.M. Gryshko National Botanical Garden of the NAS of Ukraine is analysed. As a result of screening of collection 17 cultivars of Canadian breeding, including 6 cultivars of Explorer series and 7 cultivars of Parkland series were revealed. Morphological and biological particularities of cultivars of Canadian breeding in the collection of M.M. Gryshko National Botanical Garden are studied. The evaluation of the level of their decorative value, winter hardiness and economically valuable features is made. As a result of the evaluation of cultivars according to the decorative features and economically valuable characteristics 14 cultivars of Canadian roses (Agnes, Therese Bugnet, Alexander Mackenzie, Champlain, Georges Vancouver, Henry Kelsey, John Davis, Praire Dawn, Adelaide Hoodles, Morden Blush, Praire Joy, Winnipeg Park, Hope for Humanity, Morden Sunrise) are recommended for use in landscape construction. It is concluded that Canadian cultivars of roses can become donors of such a valuable feature as winter hardiness, and therefore they are beneficial material for modern breeding research.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0010.000
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 head0.057
GPT teacher head0.242
Teacher spread0.186 · 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.

Study designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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