GENETIC CERTIFICATION OF BLACK CURRANT (RIBES NIGRUM L.) VARIETIES USING A DNA MARKER FROM RESOURCES OF THE VNIISPK
Bibliographic record
Abstract
Смородина черная (Ribes nigrum) − одна их ведущих ягодных культур в России. Популярность ее объясняется высокой, стабильной урожайностью, неприхотливостью к условиям возделывания, высоким уровнем механизации, что позволяет выращивать ее в промышленных масштабах (Князев, С.Д. и др., 2004). Ведущими производителями ягод смородины черной являются Польша, Германия и Россия. В США и Канаде смородина черная не так популярна, как в Западной Европе и России (Пикунова А.В., 2019). Black currant (Ribes nigrum) is one of the leading berry crops in Russia. Its popularity is explained by its high, stable yield, unpretentiousness to cultivation conditions, high level of mechanization, which makes it possible to grow it on an industrial scale (Knyazev, S.D. et al., 2004). The leading producers of blackcurrant berries are Poland, Germany and Russia. In the USA and Canada, blackcurrant is not as popular as in Western Europe and Russia (Pikunova A.V., 2019).
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".