COMPARATIVE EVALUATION OF PRODUCTIVITY INDICATORS OF DOMESTIC AND FOREIGN SOYBEAN VARIETIES IN THE CONDITIONS OF THE ALMATY REGION
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article presents a comparative study of six Kazakhstan-bred soybean varieties (Victory, Pamyat YGK, Lastochka, Aisaule, Zhansaya, Yelmerey) and 19 foreign varieties (Delta, Slavia, Selecta 301, Vilana, Korsak, Galina, Trijumf, Voyevodzhanka, Sava, Ascacubi, Hilario, Blamcos, Atlantic, Luna, Safrana, Santana, Sponsor, Zen, Dekabig) conducted at an ecological variety testing nursery. Among the Kazakh varieties, Yellmerey, Zhansaya, and Aisaule stood out for their high yields of 49.2 c/ha, 48.5 c/ha, and 47.3 c/ha, respectively. The top-yield foreign varieties were Voyevodzhanka from Serbia with 48.8 c/ha, Sava with 49.0 c/ha, Luna from Italy with 51.8 c/ha, and both Atlantic and Blamcos with 46.0 c/ha each. The French variety Sponsor also achieved a high yield of 51.7 c/ha. The Kazakh variety Aisaule and Italian variety Luna were notable for their high fat content at 21.9% and 22.2%, respectively. Varieties such as Victory and Aisaule from Kazakhstan, along with Delta, Selecta 301, and Vilana from Russia, Korsak from Ukraine-Canada collaboration, and Safrana from France, exhibited high protein content ranging between 38.6% and 40.6%. These outstanding varieties serve as a breeding resource for developing new, high-yield soybean varieties for the southeastern region of Kazakhstan.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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 it