Interspecific differentiation and phylogenetic relationships of poison ryegrass (<i>Lolium temulentum</i> L.) and Persian darnel (<i>L. persicum</i> Boiss. & Hohen. ex Boiss.)
Bibliographic record
Abstract
To clarify the speciation and evolution of the inbreeding Lolium spp., poison ryegrass and Persian darnel, we analyzed genetic relationships using microsatellite and AFLP markers among accessions from Pakistan, where both species grow sympatrically or parapatrically. Dendrograms were constructed using the unweighted pair-group method with arithmetic averages (UPGMA), based on simple matching coefficient of similarity among 29 accessions of poison ryegrass and 16 accessions of Persian darnel. Most of the poison ryegrass and Persian darnel accessions were genetically divided into two clusters. One and two chloroplast RFLP (restriction fragment length polymorphism) haplotypes were identified in poison ryegrass and Persian darnel accessions, respectively, from Pakistan, which correspond to each cluster or subcluster of dendrograms. Some accessions, morphologically identified as Persian darnel, belong to neither poison ryegrass nor Persian darnel clusters and locate in other cluster between them. Because this intermediate group had the same haplotype as poison ryegrass, shared almost all alleles with poison ryegrass and/or Persian darnel, and was genetically closer to poison ryegrass than to Persian darnel, we hypothesize that the intermediate group was derived maternally from poison ryegrass via hybridization with Persian darnel. Key words: AFLP, chloroplast DNA-RFLP, Lolium persicum, Lolium temulentum, microsatellite, phylogenetic analysis
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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".