Sequence characterization of the putatively sex-linked <i>Ssu72</i>-like locus in willow and its homologue in poplarThis note is one of a selection of papers published in the Special Issue on Poplar Research in Canada.
Bibliographic record
Abstract
Previous studies have identified a sequence characterized amplified region (SCAR) marker in Salix viminalis L. that appears to segregate with gender. To characterize this marker, we tested these SCAR primers in poplar ( Populus trichocarpa Torr. & A. Gray) and 12 species of willow ( Salix ). Although amplification was inconsistent with respect to species and gender, products were obtained in four willow species (but not in poplar). The resulting sequences show that the SCAR consists of (i) a length variable purine-rich repeat region and (ii) a region highly conserved between species. The conserved region has an apparent homologue in the poplar genome, where it corresponds to the putative promoter region of an Ssu72-like gene (involved in transcriptional start site regulation) on chromosome XV. We used the poplar genome sequence to design gene-anchored primers that consistently amplify this region and part of the Ssu72-like coding region in willows as well as poplars, irrespective of species and gender. The gene-anchored primers amplify a region that, while conserved, has numerous single feature polymorphisms (SFPs) both within and between species. This region could thus be used for population and phylogenetic studies.
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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 | 0.001 |
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".