THE RECONSTRUCTION OF CULTIVARE LUTZ GOLDEN APPLE GRAFTED ON M9 ROOTSTOCK
Bibliographic record
Abstract
The first intensive apple orchards in Albania were planted in 1980s. M9 was used as a rootstock and as cultivars were used Golden Delicious, Lutz Golden, Renet Canadian, Red Delicious,Granny Smith, Fuji, etc. The applied planting distance were 4 x 2.5 meters or some 100/plants for hectare with the average production performance reaching 200-250 quintals/hectare. The agrarian reform between 1992- 1998 and the changes to the ownership of the land improved the situation in the existing apple orchards creating new development opportunities. Currently, new owners invest by hiring contemporary technology thanks to financial accumulations from remittances and state projects on the agriculture. In 2000 - 2004 certain important interventions under the IP Vlore and Horticulture Department of the Agricultural University of Tirana were realized aiming at improving the situation in the existing apple planting. To mention here among others, the study of the impact of the reconstruction mass of Lutz Golden apple grafted with the M9 rootstock. The study was realized in a 2 hectare area with apple trees aged almost 20 years. Technically, the experiment was raised by 5 variants X 4 replication/variant where V0 stands for control variants, V1 stands for lowering of aura by 10%, V2 stands for lowering of aura by 20%, V3 stands for lowering of aura by 30%, and V4 stands for reconstruction in mass by 70% and reformation of aura in three consecutive years. In the end, the best variants where found to be V4 45. 23 and V3, 33.12 kilograms for each apple tree where the utilized schemes optimized the vegetative-production situation in the apple orchards in an effective way.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".