Проучване на някои растежни параметри при черешови сортове в района на град Пловдив
Bibliographic record
Abstract
The study was conducted in an experimental orchard on the territory of the Fruit Growing Institute - Plovdiv. Some growth characteristics were monitored in eight sweet cherry cultivars: Lapins, Canada Giant, Ferrovia, Regina, Kordia, Skeena, Samba, and Van. The investigated parameters were: height (m) and volume (m3) of the tree canopy, trunk cross-sectional area (TCSA, cm2), length of one-year shoot (cm), length (cm), number of may bouquets and number of fruit buds on two- and three-year-old branches. In terms of the volume of the canopy, the largest values were found in the Kordia (16.9 m3) and Van (16.3 m3) cultivars, while the Skeena cultivar stood out with the smallest volume - 6.3 m3. Trunk cross-sectional area (TCSA) was the largest in the Van cultivar with 316.1 cm2, followed by the Lapins cultivar - 295.9 cm2, and the lowest TCSA value was the Skeena cultivar (178.0 cm2). The average length of the one-year shoot varies from 26.8 cm (Ferrovia) to 49.6 cm (Lapins), of the two-year-old branch - from 15.5 cm (Regina) to 32.2 cm (Lapins), and of the three-year-old branch - from 17.9 cm in the Canada Giant cultivar to 32.3 cm at Skeena cultivar. A greater number of may bouquets and fruit buds (except for the Regina cultivar) on the two-year-old branch was found in all studied cultivars. In both types of branches, the lowest values in terms of the number of may bouquets and fruit buds were recorded in the Kordia cultivar and the highest in the Van cultivar.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".