A framework linkage map of perennial ryegrass based on SSR markers
Bibliographic record
Abstract
A moderate-density linkage map for Lolium perenne L. has been constructed based on 376 simple sequence repeat (SSR) markers. Approximately one third (124) of the SSR markers were developed from GeneThresher libraries that preferentially select genomic DNA clones from the gene-rich unmethylated portion of the genome. The remaining SSR marker loci were generated from either SSR-enriched genomic libraries (247) or ESTs (5). Forty-five percent of the GeneThresher SSRs were associated with an expressed gene. Unlike EST-derived SSR markers, GeneThresher SSRs were often associated with genes expressed at a low level, such as transcription factors. The map constructed here fulfills 2 definitions of a "framework map". Firstly, it is composed of codominant markers to ensure map transferability either within or among species. Secondly, it was constructed to achieve a level of statistical confidence in the support-for-order of marker loci. The map consists of 81 framework SSR markers spread over 7 linkage groups, the same as the haploid chromosome number. Most of the remaining 295 SSR markers have been placed into their most likely interval on the framework map. Nine RFLP markers and 1 SSR marker from another map constructed using the same pedigree were also incorporated to extend genome coverage at the terminal ends of 5 linkage groups. The final map provides a robust framework with which to conduct investigations into the genetic architecture of trait variation in this commercially important grass species.
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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) | 0.001 | 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".