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Record W4312273184 · doi:10.2478/prolas-2022-0069

Evaluation of <i>Ribes Rubrum</i> Cultivars in Estonia

2022· article· en· W4312273184 on OpenAlexfundno aff
Toivo Sepp, Reelika Rätsep, A. Libek, A. Kikas

Bibliographic record

VenueProceedings of the Latvian Academy of Sciences Section B Natural Exact and Applied Sciences · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsnot available
FundersEesti MaaülikoolMinistry of Rural Affairs
KeywordsRibesCultivarBrixAscorbic acidTitratable acidRipeningHorticultureBerryYield (engineering)BiologyBotanyFood scienceSugar

Abstract

fetched live from OpenAlex

Abstract The evaluation of cultivars of red and white currant ( Ribes rubrum L.) was carried out in 2019–2020 at the Polli Horticultural Research Centre of the Estonian University of Life Sciences, South-Estonia. The aim of this study was to estimate traits of red and white currant cultivars of both Estonian and introduced origin. An evaluation plot was established in the autumn of 2016. During two consecutive years (2019–2020), 11 promising cultivars were evaluated for the beginning of flowering and fruit ripening, winter hardiness, resistance to diseases (expressed in scores 1–9), yield per bush, fruit weight, drop of flowers and premature berries, as well as the content of the soluble solids (°Brix), titratable acids, ascorbic acid, total phenols and total anthocyanins. The highest yield was determined in cultivars ‘Bayana’ and ‘Viksnes’, while cvs. ‘Rovada’, ‘Jonkheer van Tets’, ‘Kurvitsa 4’ and ‘Valko’ had larger berries. The highest soluble solid content was found in the berries of red currant ’Krameri punane’ (13.8 °Brix) and white currant ’Bayana’ (12.4 °Brix).

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)0.005
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.292
Teacher spread0.239 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Latvian Academy of Sciences Section B Natural Exact and Applied SciencesSame topicBerry genetics and cultivation researchFrench-language works237,207