Bibliographic record
Abstract
Abstract The aim of the study was to identify the sources of economically useful traits of winter wheat from the collection of the Federal State Budgetary Scientific Institution “Federal Research Center All-Russian Institute of Plant Genetic Resources N.I. Vavilov ”(VIR) for adaptive breeding of this crop in the Middle Cis-Ural region. Highly productive varieties Harvard (k-66051 USA), Rasad (k-66087 Kazakhstan), Augusta (k-63929 Rostov region), Dominanta (k-64620 Rostov region) and AC Buteo (k-66054 Canada) were the most adaptive according to the method of L.A. Zhivotkova, Z.A. Morozova, L.I. Sekatueva (1994). But they were characterized by significant yield variability (V=36-130 %). Varieties Nastya (k-65675 Stavropol), WA007970 (k-66043 USA), AC Buteo, PA8769-158 (k-65943 USA), Ransom (k-65236 USA) and Farnum (k-65944 USA) showed high homeostaticity (Hom = 1.8-24.7). These varieties were the most productive and stable also according to the method of E.D. Nettevich, A.I. Morgunova, M.I. Maksimenko (1985). Varieties AC Buteo (6), WA007970 (15), PA8769-158 (16), Farnum (21), Ransom (21), Nastya (22) were distinguished by the sum of ranks; the sum of the ranks of the standard Moskovskaya 39 was 22. Sources of increased grain size (weight of 1000 grains 41.2-54.0 g) were identified - varieties Nemchinovskaya 17 (k-65756), Harvard, Rasad, Nureke (k-66088), Alija (k-66089), Avesta (k- 64491), Agra (k-64492), Shestopalivka (k-65060); grain content of a ear (30.9-47.3 pcs.) - Dzhangal (k-65610), Slavitsa (k-65656), Nastya, Alija. High grain glassiness of 90-100% for two years of study (2019-2020) was obtained in varieties Nastya, Farnum, WA007970, AC Buteo and Ransom.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".