Analysis of relationships between<i>Aegilops tauschii</i>and the D genome of wheat utilizing microsatellites
Bibliographic record
Abstract
Sixty Aegilops tauschii accessions and 60 European hexaploid wheat varieties were analyzed with 14 wheat microsatellite (WMS) primer sets to (i) study the phylogeny of Ae. tauschii, (ii) search for a specific genotype of Ae. tauschii most closely related to the D genome of hexaploid wheat, and (iii) narrow down the presumed birthplace of the latter. An average of 6.5 and 4.0 alleles per locus was detected in Ae. tauschii and in wheat, respectively. The highest genetic diversity of Ae. tauschii was found in Transcaucasia and southeast of the Caspian Sea. Distribution of the 87 alleles (without null alleles) found in Aegilops did not allow differentiation of the species into the two subspecies strangulata and tauschii. Excluding null alleles, 41 alleles occurred parallel in wheat and in Aegilops. Data obtained in this study supports the view of the D genome of hexaploid wheat being a composite of several sources but does not support subsp. strangulata as the possible major source of the D genome. The highest number of region-specific alleles (three) in Ae. tauschii occurring also in the D genome of wheat, and therefore most indicative for its evolution was found in present-day Georgia, where subsp. strangulata is not endemic.
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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".