[The high-molecular glutenins of the soft winter wheats from European countries and their relationship to the glutenin composition of the ancient and modern wheat varieties of Ukraine].
Bibliographic record
Abstract
The sources of high-quality components of HMW glutenines determining grain quality, as initial material for breeding in the conditions of Ukraine were revealed on the base of analysis of 75 literature sources data about composition of high-molecular weight (HMW) glutenin and pedigrees of 598 European wheats from 12 countries, bred in 1923-1997, including, 449 cultivars from West and 149 East Europe. Origin of these components was observed in varieties of Great Britain, France and Germany from ancient Ukrainian wheat Red Fife and it derivative spring wheats of Canada--Marquis, Garnet, Regent, Saunders, Selkirk and of USA--spring wheat Thatcher and winter wheats--Kanred and Oro--as directly as via cultivars of European countries and Australia; in wheats of East European countries from winter wheats Myronivs'ka 808 and Bezostaya 1 (derivative of Ukrainian cultivars Ukrainka and Krymka) and their descendants; in wheats of Austria and Italy--from the both genetical sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".