ASSESSMENT OF GENOTYPES OF YARN BARLEY FROM THE COLLECTION OF VIR FOR ADAPTIVITY AND PRODUCTIVITY UNDER CONDITIONS OF EASTERN SIBERIA
Bibliographic record
Abstract
The results of a comprehensive assessment were analyzed for 238 samples of the world collection of VIR named after N.I. Vavilov for 2014-2017 years on the yield and the degree of its variation (Cv,%), stress stabil-ity (Уmax-Уmin), ecological stability (St2) and plasticity (bi), relative stability of genotypes (Sgi), general and specific adaptive capacity (GАСi, SАСi), selection value genotypes (SVGi), the adaptation coefficient (CA). It is established that the greatest grain productivity was received from Codac, Etienne, Diamond, AC Albright (Canada), Vaughn C.I. 11367, Kindred (USA), Bagretz (Sverdlovsk region), Ubagan (Chelyabinsk region), Talan, Tanay (Novosibirsk region) and Abalak (Krasnoyarsk territory, Tyumen region). A low coefficient of variation in yield was observed in varieties – Koral (USA), AC Albright (Canada), Domen (Norway), Cirstin (Germany), Asem (Kazakhstan), Nutans 302 (Samara region), Zernogradets 770 (Rostov region) Yasny (Ros-tov region), Novichok (Kirov region), Pervotselinnik (Orenburg region), Tarsky 3 (Omsk region), Abalak (Krasnoyarsk territory, Tyumen region). Among varieties with an increased breeding value of genotypes (SVGi) for the "grain mass with m2" attribute are – AC Albright (Canada), Cirstin (Germany), Talan (Novosi-birsk region), Tarsky 3 (Omsk region), Abalak (Krasnoyarsk territory, Tyumen region). High responsiveness to improving the growing conditions ar noticed among Duplex C.I. 2433, Kindred, Heritage, Hazen (USA), Loyolla, Jackson, BVP-2D-1, AC Stacey, CDC Mc Gwire (Canada), Sv. 66905, Kinnan (Sweden), Mojar (Norway), Bingo Carlsberg (Denmark), M 1913/88 (Czechoslovakia), Olbram (Czech republic), Margret (Germany), Phoenix, Corona, Kozak, Effect, Symphony, Harmony (Ukraine), Hadjibey (Belorussia), Ilek 16 (Kazakhstan), Tonus (Rostov region), Binom (Sverdlovsk region), Raushan (Moscow region), Siberian avangard (Omsk region), Kolchan (Altai 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".