IMPACT OF CLIMATE FACTORS ON YIELD AND QUALITY OF VINE VARIETY CABERNET SAUVIGNON IN PODGORICA WINE GROWING REGION
Bibliographic record
Abstract
The influence of climatic factors on grape yield, grape cluster weight, sugar and acidity content in stum in variety Cabernet Sauvignon was measured in period from 2011 to 2013 at the experimental field of Biotechnical Faculty in Podgorica.The study was conducted in the vineyard of the Biotechnical Faculty in Podgorica in the stage of full grape maturity.The highest grape yield as well as the cluster weight were measured in 2012 (1.2 kg/m 2 and 125 g respectively), while the lowest values were measured in 2013 -0.88 kg/m 2 and 92 g.Highest sugar content in stum was measured in 2011, and lowest in 2013.The highest acid content was measured in 2013 (6.50 g/l) as a result of heavy rainfall during the growing season, especially in August and September.Differences between the studied parameters were statistically significant.The results showed that the yield and quality of grapes were in direct relation with the weather conditions in certain years of experiments.
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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 | 0.000 |
| 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".