Regional patterns of microsatellite diversity in Ethiopian tetraploid wheat accessions
Bibliographic record
Abstract
Abstract This study was conducted to assess regional patterns of diversity of Ethiopian tetraploid wheat accessions and to identify areas of diversity that can be used as source of new germplasm for developing high yielding and stable varieties. A collection of 133 Ethiopian tetraploid wheat accessions and eight introduced cultivars was analysed using 29 wheat microsatellite markers. A total of 383 alleles were detected with an average value of 13.14 alleles per locus. Relatively more alleles were observed in the B genome than in the A genome. Gene diversity indices ranged from 0.08 to 0.95, with a mean value of 0.72. Accessions collected from the same region were pooled and the number of alleles and gene diversity were calculated over the 29 simple sequence repeats for each region. Higher numbers of alleles were detected in the Shewa region (8.72), followed by Tigray (5.86) and Hararghe (5.76). The highest average gene diversity value was found in Shewa (0.65), followed by Gondar (0.64). No significant correlation was observed between geographic distance and genetic distance. Out of 383 different alleles detected, 93 (24.4%) were observed to be region‐specific. Region‐specific alleles were found across all chromosomes except for Xgwm752 , Xgwm155 and Xgwm148 . Genetic similarity coefficients were estimated for all the possible 55 pairs of regional comparisons and they ranged from 0.16 to 0.52, with a mean value of 0.50. All provinces were differentiated in the UPGMA cluster diagram.
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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 | 0.002 | 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".