Evaluation of <i>Ribes Rubrum</i> Cultivars in Estonia
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".