Ecological stability of triticale samples in the conditions of the Khabarovsk territory
Bibliographic record
Abstract
Abstract The new grain crop triticale is of great interest for cultivation in the soil and climatic conditions of the middle Amur Region; therefore, this study assessed the environmental stability of yield formation for a collection of triticale samples. The varieties with the maximum yields identified in the study were the following: AC Certa (Canada), Lana (Belarus), Dagvo (Russia), Golden Scallop (Russia), Ulyana (Belarus), Uzor (Belarus), Lotos (Belarus), Mykola (Ukraine), Victoria (Ukraine), Sandio (Switzerland), Wanad (Poland) and Yarik (Russia). The AC Certa (Canada) variety was characterised by high demands on growing conditions (St2 = 0.69, A = 30.03) and unstable yield (1.8-7.0 t/ha). The Victoria (Ukraine) variety was characterised by high ecological stability of yield (St2 = 0.99, A = 27.45) in various years (2.5-3.1 t/ha). Results indicated that the yield formation of the collection samples were strongly dependent on weather conditions (R=0.554). Lastly, a model of spring triticale yield formation dependent on weather factors was constructed using regression analysis. The most significant climatic factor was photosynthetically active radiation during the active vegetation period
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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 | 0.001 | 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".