Characterization of chromosome-specific S-SAP markers and their use in studying genetic diversity in <i>Aegilops</i> species
Bibliographic record
Abstract
The short interspersed nuclear element (SINE), Au, was used to develop sequence-specific amplified polymorphism (S-SAP) markers for U- and M-genome chromosomes. The markers were localized using Triticum aestivum (wheat)-- Aegilops geniculata and wheat-- Aegilops biuncialis disomic chromosome addition lines. Thirty-seven markers distributed over 6 U and 6 M chromosomes were produced. A genetic diversity study carried out on 37 accessions from Ae. biuncialis, Ae. comosa, Ae. geniculata, and Ae. umbellulata suggested that Ae. biuncialis have arisen from its diploid ancestors more recently than Ae. geniculata. Several earlier studies indicated that the M genomes in polyploid Aegilops species had accumulated substantial rearrangements, whereas the U genomes remained essentially unmodified. However, this cannot be attributed to the preferential insertion of retroelements into the M genome chromosomes. Fourteen markers from a total of 8 chromosomes were sequenced; 3 markers were similar to known plant genes, 1 was derived from a long terminal repeat (LTR) retrotransposon, and 10 markers did not match to any known DNA sequences, suggesting that they were located in the highly variable intergenic regions.
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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 | 0.000 |
| 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) | 0.001 | 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".