Characterization of 20 new EST-SSR markers for northern red oak (Quercus rubra L.) and their transferability to Fagus sylvatica L. and six oak species of section Lobatae and Quercus
Bibliographic record
Abstract
Northern red oak (Quercus rubra L.) is widely distributed in the eastern United States and southeastern Canada. It has also been introduced to Europe, where it has become an economically important plantation species now. Despite growing genomic resources, the number of available EST-SSR (expressed sequence tag – simple sequence repeat) markers for Q. rubra is still limited. Here, we used existing sequence information to provide a new set of EST-SSRs for northern red oak. In total, we report 20 polymorphic EST-SSRs, for which performance was evaluated in three Q. rubra populations from different regions in Michigan. We further tested the transferability of these markers to six additional oak species of section Lobatae (Quercus ellipsoidalis E.J. Hill, and Quercus georgiana M.A. Curtis) and Quercus (Quercus robur L., Quercus alba L., Quercus pedunculiflora K. Koch, and Quercus petraea (Matt.) Liebl.), as well as to European beech (Fagus sylvatica L.). The reported markers can be used in future population genetic 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 | 0.000 | 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".