ORGANIZATION OF A MOTHER PLANTATION OF AMERICAN CRANBERRY ON SHELTERED GROUND
Bibliographic record
Abstract
The article presents the results of work on the organization of a mother plantation of largefruited cranberry varieties and the first two years of its cultivation. Cranberry is of a great value in human nutrition due to its high nutritional value and unique medicinal value. In addition, increasing economic activity leads to a reduction in the area of natural berry fields, including cranberry. Under these conditions, industrial cultivation of cranberries has not only commercial value, but also can reduce the recreational load on natural ecosystems. The experience of plantation cultivation of cranberry in the United States, Canada, Germany, Sweden, Poland, and Belarus testifies to the high efficiency of its cultivation: yields on plantations are dozens or even hundreds of times higher than in natural thickets. The research was carried out in years 2018-2019 on the sheltered ground at the Far East Research Institute of Agriculture of the Russian Academy of Sciences. Object of research: survival rate of cranberry planting material of Stevens, Ben Lear, McFarlin, and Pilgrim varieties. The paper provides data on the survival rate and length of growth of shoots of these varieties. The survival rate of Stevens variety’s cuttings with length of about 6 cm amounted to about 52% on average, and the survival rate of longer (9-12 cm) cuttings of Ben Lear variety amounted to 65 %. In 3 months after planting, the average growth of cranberry shoots of Stevens variety amounted to about 5 cm. As for the Ben Lear variety, the growth in 1.5 months after planting averaged about 3 cm. According to the growth of creeping shoots for the period May – September, 2019, the varieties were arranged in descending order as follows: Ben Lear, Stevens, Pilgrim, McFarlin. The maximum average growth of creeping shoots was noted in the Ben Lear variety 65±8 cm, and the minimum values were 46±3 cm in the McFarlin variety.
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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 | 0.001 | 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) | 0.002 | 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".