A Simple Sequence Repeat-Based Linkage Map of Barley
Bibliographic record
Abstract
A total of 568 new simple sequence repeat (SSR)-based markers for barley have been developed from a combination of database sequences and small insert genomic libraries enriched for a range of short simple sequence repeats. Analysis of the SSRs on 16 barley cultivars revealed variable levels of informativeness but no obvious correlation was found with SSR repeat length, motif type, or map position. Of the 568 SSRs developed, 242 were genetically mapped, 216 with 37 previously published SSRs in a single doubled-haploid population derived from the F(1) of an interspecific cross between the cultivar Lina and Hordeum spontaneum Canada Park and 26 SSRs in two other mapping populations. A total of 27 SSRs amplified multiple loci. Centromeric clustering of markers was observed in the main mapping population; however, the clustering severity was reduced in intraspecific crosses, supporting the notion that the observed marker distribution was largely a genetical effect. The mapped SSRs provide a framework for rapidly assigning chromosomal designations and polarity in future mapping programs in barley and a convenient alternative to RFLP for aligning information derived from different populations. A list of the 242 primer pairs that amplify mapped SSRs from total barley genomic DNA is presented.
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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 | 0.001 |
| 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) | 0.004 | 0.003 |
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".