ddRAD-seq generated genomic SNP dataset of Central and Southeast European Turkey oak (Quercus cerris L.) populations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Turkey oak ( Quercus cerris L.) is one of the most ecologically and economically significant deciduous tree species in the Central and Southeast European regions. The species has long been known to exhibit high levels of genetic and phenotypic variation. Recent climate response predictions for Turkey oak suggest a significant distribution extension in Europe under climate change. Since Turkey oak has relative drought-tolerant behaviour, it is regarded as a potential alternative for other forest tree species during forestry climate adaptation efforts, not only in its native regions but also in Western Europe. For this reason, the survey of existing genetic variability, genetic resources, and adaptability of this species has great significance. Next-generation sequencing approaches, such as ddRAD-seq (Double digest restriction-site associated DNA sequencing), allow the attainment of high-resolution genome-wide single nucleotide polymorphisms (SNPs). This study provides the first highly variable genome-wide SNP data for Turkey oak generated by ddRAD-seq. The dataset comprises 17 607 de novo and 26 059 reference mapped SNPs for 88 individuals from eight populations, two from Bulgaria, one from Kosovo, and five from Hungary. Reference mapping was carried out by using cork oak’s ( Quercus suber L.) reference genome. The obtained high-resolution genome-wide markers are suitable for investigating selection and local adaptation and inferring genetic diversity, differentiation, and population structure. The dataset is accessible at: https://doi.org/10.5281/zenodo.8091252
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it