Geographical variation in random amplified polymorphic DNA and quantitative traits in Norway spruce
Bibliographic record
Abstract
Quantitative traits and random amplified polymorphic DNA variations were investigated on the whole natural range of Norway spruce (Picea abies (L.) Karst.). Results showed that the species can be separated into two main groups (northern and central Europe) using both types of characters. Such spatial and geographical fragmentation of species natural range rarely occurs in conifers and is consistent with prolonged geographical isolation within two refugial zones located in distinct environmental conditions (Moscow area and east of central European mountains). Within each of these two infraspecific groups, we revealed an apparent uncoupling between quantitative traits (related to growth, phenology, and wood quality) and DNA. However, the combination of both molecular and quantitative traits information provided new insights about geographical patterns of variation: a dominant latitudinal gradient was found in the Baltico-Nordic domain contrasting markedly with the main eastwest migration expected from pollen data, while in central Europe, a noticeable longitudinal gradient was congruent with eastwest migration. The concordance and discrepancies between quantitative traits and DNA are discussed in terms of historical events in P. abies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".