Genetic Divergence in Domesticated and Non-Domesticated Gene Regions of Barley Chromosomes
Bibliographic record
Abstract
Little is known about the genetic divergence in the chromosomal regions with domesticated and non-domesticated genes. The objective of our study is to examine the effect of natural selection on shaping genetic diversity of chromosome region with domesticated and non-domesticated genes in barley using 110 SSR markers. Comparison of the genetic diversity loss between wild and cultivated barley for each chromosome showed that chromosome 5H had the highest divergence of 35.29%, followed by 3H, 7H, 4H, 2H, 6H. Diversity ratio was calculated as (diversity of wild type - diversity of cultivated type)/diversity of wild type×100%. It was found that diversity ratios of the domesticated regions on 5H, 1H and 7H were higher than those of non-domesticated regions. Diversity ratio of the domesticated region on 2H and 4H is similar to that of non-domesticated region. However, diversity ratio of the domesticated region on 3H is lower than that of non-domesticated region. Averaged diversity among six chromosomes in domesticated region was 33.73% difference between wild and cultivated barley, and was 27.56% difference in the non-domesticated region. The outcome of this study advances our understanding of the evolution of crop chromosomes.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".