Study of samples of spring barley from the collection of the All-Russian institute of crop production for resistance to biotic stress
Bibliographic record
Abstract
Abstract Spring barley in Eastern Siberia occupies an important place among the main grain crops and is grown mainly for fodder purposes. Its grain can also be used in bakery, confectionery, pharmaceutical and other industries. In addition, barley is the main raw material for brewing. One of the reasons that have a significant impact on the formation of the yield and technological qualities of barley is the high susceptibility of the crop to phytopathogenic microflora, the strong development of which leads to their decrease. Barley is the most affected crop of the cereal group. The most common diseases are root rot, represented mainly by pathogens of the fusarium - helminthosporium complex. Fungi of the genus Bipolaris were identified in the forest-steppe zone, in the subtaiga zone - species of the genus Fusarium. Both are capable of infecting almost all underground and aboveground plant organs. According to the long-term data, root rot annually reduces grain yield by 20 - 23%. Samples of barley with resistance to damage by dark brown and striped barley spotting (7 points, reaction type - R) were identified; Heritage (USA), Condor, AC Albright (Canada), Malva (Latvia), Wash, Symphony (Ukraine), Viner (Kirov region), Pervocelinnik (Orenburg region), Vorsinsky 2 (Altai region) and Zauralsky 1 (Tyumen region).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".