ДОСТИЖЕНИЯ ФНЦ ИМ. И. В. МИЧУРИНА В СЕЛЕКЦИИ ЯГОДНЫХ И НЕТРАДИЦИОННЫХ САДОВЫХ КУЛЬТУР ЗА 2019–2023 ГГ.
Bibliographic record
Abstract
Подведены результаты исследований по селекции ягодных и нетрадиционных садовых культур в отделе ягодных культур ФГБНУ «ФНЦ им. И. В. Мичурина» за 2019–2023 гг. За указанный период сотрудниками отдела созданы 13 новых сортов, в том числе: Берендей, Гирлянда, Жита, Поклон Сибири (жимолость); Аббат (кизил); Гермес, Спартак (крыжовник); Абиссинка, Аксинья (смородина черная); Хельга (смородина красная), Пиковая дама (смородина золотистая); Юбилей наукограда (хеномелес); Сиеста (шелковица). Допущены к использованию в производстве 12 сортов ягодных и нетрадиционных садовых культур селекции Центра: Мулатка (арония); Мичуринец (барбарис); Антошка (жимолость); Сластёна (ирга); Искушение (калина); Аббат (кизил); Аристократ (крыжовник); Казанова, Янтарная ягода (облепиха); Августовская ночь (смородина золотистая); Аксинья, Амирани (смородина черная). The paper presents the research results on breeding of berry and non-traditional crops in department of berry crops of the FSBSI “FSC named after I. V. Michurin” in the period of 2019– 2023. The given period allowed our scientists to create 13 new varieties including ‘Berendey’, ‘Girlyanda’, ‘Zhita’, ‘Poklon Sibiri’ (honeysuckle); ‘Abbat’ (dogwood); ‘Germes’, ‘Spartak’ (gooseberry); ‘Abissinka’, ‘Aksin’ya’ (black currant), ‘Khelga’ (red currant); ‘Pikovaya Dama’ (golden currant); ‘Yubiley Naukograda’ (chaenomeles); ‘Siesta’ (mulberry). 12 varieties of berry and non-traditional garden crops of the Center's selection have been approved for use in the production: ‘Mulatka’ (chokeberry); ‘Michurinets’ (barberries); ‘Antoshka’ (honeysuckle); ‘Slastena’ (saskatoon berry); ‘Iskusneniye’ (viburnum); ‘Abbat’ (dogwood); ‘Aristokrat’ (gooseberry); ‘Kazanova’, ‘Yantarnaya Yagoda’ (sea- buckthorn); ‘Avgustovskaya Noch’’ (golden currant); ‘Aksin’ya’, ‘Amirani’ (black currant).
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.046 | 0.020 |
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".