Comparative analysis of genetic diversity between Qinghai-Tibetan wild and Chinese landrace barley
Bibliographic record
Abstract
Fifty-two SSR markers were used to evaluate the genetic diversity of 33 Qinghai-Tibetan wild barley accessions, 56 landraces collected primarily from other parts of China, and 1 Israeli wild barley accession. At the 52 SSR loci, 206 alleles were detected for the 90 accessions, among which 111 were common alleles. The number of alleles per locus ranged from 1 to 9, with an average of 4.0. Polymorphism information content (PIC) values ranged from 0 to 0.856 among all the markers, with an average of 0.547. The PIC value of Qinghai-Tibetan wild barley varied from 0 to 0.813 with an average of 0.543, while in landraces, the markers showed a range of 0 to 0.790 with an average of 0.490. The SSR markers could clearly differentiate the Qinghai-Tibetan wild barley from the landraces. Twenty-four unique alleles were observed in Qinghai-Tibetan wild barley, and the frequency of unique alleles in Qinghai-Tibetan wild barley was about 2.1 times higher than that in the landraces, on average. Five of the 7 chromosomes had more unique alleles in the Qinghai-Tibetan wild barley, but chromosome 2H had more unique alleles in the landraces. The presence of many unique alleles may reflect the adaptation of this barley germplasm to diverse environments and production systems.
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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 | 0.002 |
| 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".