Variability of nitrogen and carbon contents in the needles of Canadian Douglas-fir provenances of two soil types in Serbia.
Bibliographic record
Abstract
Seed transfer and introduction risks can be reduced by setting up provenance tests and studying the elements of genotypic, phenotypic, physiological, and anatomical structure. Forest tree increment and productivity depend on photosynthesis and the concentrations of nitrogen and carbon in the needles. With the aim of introducing Douglas-fir into Serbia, the Institute of Forestry in Belgrade established several experimental provenance tests to assess the genetic ability of Douglas-fir to adapt to new environmental conditions in Serbia. The provenance tests included fourteen different Douglas-fir provenances originating from Canada. All the trees of the study provenances were of the same age and grown in the same conditions, but on two different soil types: eutric cambisol and vertisol. There was considerable variability of nitrogen and carbon contents in the needles of all tested provenances on both locations. This variability was used as the basis for the study of the intensity and dynamics of the physiological processes of Douglas-fir mineral nutrition as indicators of its capacity to adapt to the sites in Serbia. All Douglas-fir provenances planted on eutric cambisol had higher contents of nitrogen and lower contents of carbon, i.e. narrower C/N ratios than the provenances planted on vertisol. The differences resulted from different conditions for Douglas-fir physiological activity and nutrition in the two types of soil.
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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 | 0.001 | 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".