New sweet cherry cultivars in intensive plantings
Bibliographic record
Abstract
The study took place in the largest sweet cherry plantation in West Hungary. The purpose has been the identification of those varieties, which will be suitable for intense cultivation, early fruiting and excellent fruit quality, moreover, the selection of the optimal phytotechnical procedures. At the same time, scion-rootstock combinations have been tested also from the point of view of growing intensity and fruiting in high-density plantation. The dense planting is induced to start fruiting early and yield regularly by special methods.Yielding was stimulated by maintaining the balance of vegetative-generative growth by binding the shoots, by summer pruning, by cuts on the trunk and root pruning. Best experiences have been found in yield and quality in the following varieties: Canada Giant, Carmen, Firm Red, Giant Red, Katalin, Kordia, Regina. Dense planting has been feasible also on vigorous rootstock, like P. mahaleb. Dwarfing rootstocks like P-HL-A, Gisela 6, accelerate the formation of flower buds and yielding earlier with fruits of adequate size. ‘Firm Red’ and ‘Giant Red’ excelled with their large fruit (>27 mm diameter) in all combinations, thus being promising under Hungarian conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".