The behaviour of some peach cultivars pertaining to the peach world collection in pedoclimatic conditions of Timisoara area.
Bibliographic record
Abstract
Peach represents one of the most appreciated fruit tree variety of the temperate climate, which in the last 30 years has benefited of a special attention, fact that has led to the expansion of cultivated areas with this variety and to diversification of the assortment. Researches carried out in USA, Canada, France, Italy, Spain, even in our country had led to obtaining a large number of varieties with remarkable agro-productive characteristics. In the present work were studied 9 cultivars of peach pertaining to the Peach and Nectarine World Collection introduced and multiplied in Romania by Acad. Dr. Vasile Cociu. The cultivars originating from all continents have been planted in Timisoara in 2007 with the purpose of being tested in culture and naturalizing in Romania of some new foreign varieties. Regarding the fruit weight were evidenced 'Yinquing', 'Giala di Roma', 'Tardiva', 'Eureka' and 'Piros Magdalena'. In terms of % kernel were highlighted 'Giala di Roma Tardiva', 'Marqueen' and 'Gold Dust' cultivars with less than 7% kernel %. Concerning dry substances, the highest sugar content was registered in the fruits of following cultivars: 'Marqueen', 'Eureka', 'Yinquing' and 'Giala di Roma Tardiva'.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".