New varieties of apple trees in the assortment Central Black Earth Region of Russia
Bibliographic record
Abstract
In VNIISPK оver the past thirty years, 21 summer varieties of apple trees have been identified, of which 11 varieties are zoned in the Central Black Earth region of Russia: Orlinka, Augusta, Darena, Early Aloe, Maslovskoye, Yablochny Spas, Orlovim, Osipovskoye, Joy of Nadezhda, Zhelannoe, Yubilyar. Objective. To study the features of growth and fruiting of new summer varieties of apple trees on a medium-sized rootstock 54-118. The objects of research are summer varieties of apple trees bred at FGBNU VNIISPK (Orel city) - Avgusta, Daryona, Maslovskoye, Osipovskoye, Zhilinskoye, Spasskoye, Yablochny Spas and the control variety of Canadian selection Melba on a medium-sized clonal rootstock 54-118. Garden planting - 2014, garden planting scheme 5?2 m. When studying the strength of the growth of trees, it was revealed that the tallest trees (age 6 years) were in the varieties Apple Spas - 3.0 m and Osipovskoe - 2.9 m on a medium-sized rootstock 54-118. In 2021, Spasskoye had the highest yield - 26.2 kg/tree, Yablochny Spas Spas - 25.0 kg/tree. The largest yields on average over four years were produced by apple varieties immune to scab on a medium-sized rootstock 54-118: Zhilinskoye - 10.7 t/kg, Maslovskoye - 12.5 t/kg, Yablochny Spas - 13.6 t/kg and Spasskoye - 16.3 t/kg. When calculating the load of the crop per unit area of the crown projection, crown volume and cross-sectional area of the bole, the Maslovskoye variety turned out to have high rates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 source (direct Gemma or distilled Codex), 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".