Chloroplast microsatellite analysis reveals the presence of population subdivision in Norway spruce (<i>Picea abies</i>K.)
Bibliographic record
Abstract
Three chloroplast microsatellites (cpSSRs), previously sequence characterized and for which paternal inheritance was tested and confirmed, were used to assess their usefulness as informative markers for phylogeographic studies in Norway spruce (Picea abies K.) and to detect spatial genetic differentiation related to the possible recolonization processes in the postglacial period. Ninety-seven populations were included in the survey. Some 8, 7, and 6 different size variants for the three cpSSRs, respectively, were scored by analysing 1105 individuals. The above 21 variants combined into 41 different haplotypes. The distribution of some haplotypes showed a clear geographic structure and seems to be related to the existence of different refugia during the last glacial period. The analysis of chloroplast SSR variation detected the presence of two main gene pools (Sarmathic-Baltic and Alpine--Centre European) and a relatively low degree of differentiation (RST of about 10%), characteristic of tree species with large distribution and probably influenced by an intensive human impact on this species. Based on our data, we were not able to detect any evidence concerning the existence of additional gene pools (e.g., from Balkan and Carpathian glacial refugia), though we cannot exclude the existence of genetic discontinuity within the species' European range. A large proportion of population-specific haplotypes were scored in this species, thus indicating a possible usefulness of these markers for the identification of provenances, seed-lots, and autochthonous stands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".