Estimation of the parameters of the ecological adaptability of the alfalfa samples according to the traits ‘green mass productivity’ and ‘raw protein percentage’
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Bibliographic record
Abstract
The current paper has presented the estimation results of ecological adaptability of the alfalfa samples. The purpose of the work was to assess the productivity and quality of green mass of the alfalfa samples from the IPI plant genetic resources gene bank and to identify the most adaptive ones according to the trait ‘green mass productivity’ and ‘raw protein percentage’. The study of the collection alfalfa samples was carried out in the southern part of the Rostov region on the plots of the “ARC “Donskoy” in the breeding crop rotation of perennial grasses in 2016–2018. The objects of study were 30 alfalfa samples from the collection of N.I. Vavilov IPI from different countries (Canada, the USA, Peru, France). The variety ‘Rostovskaya 90’ was used as a standard one. The estimation of alfalfa samples on the presence of adaptive properties in them according to the trait ‘green mass productivity’ showed that the most valuable samples in present practical breeding work are the samples ‘K-32873’, ‘K-33299’, ‘K-42684’, ‘K-42249’, ‘K-78803’ with weak responsiveness to changes in environmental conditions; the samples ‘K-36104’, ‘K-48778’, ‘K-42694’, ‘K-45715’, ‘K-47800’, ‘K-47802’, ‘K-43260’ with high resistance to stress; the samples ‘K-43272’, ‘K-50545’, ‘K-47806’, ‘K-47807’ with genetically flexible genotypes. When breeding according to the trait ‘raw protein percentage’, the samples ‘K-47807’, ‘K-47804’, ‘K-42712’ possessing a high raw protein percentage and resistance to changes in this trait are important for further work.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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