Variability of seedlings of Douglas-fir provenances introduced from Canada
Bibliographic record
Abstract
Introduction of Canadian provenances of Douglas-fir (Pseudotsuga menziesii Mir / Franco) in Serbia started with the first phase of testing their genetic potential by studying the effects of geographic characteristics of the locations from which the provenances originated (latitude, longitude and altitude) on the variability of the measured seedling properties. In the laboratory of the Institute for Forestry in Belgrade, germinability of Douglas-fir seeds was tested on the germination table ("Copenhagen table" or "Jakobson table") by the standards of ISTA. The analysis of variance and the regression and correlation analysis were applied in the study of the effects of geographic parameters of Canadian provenance locations on the variability of seedlings. The results show that there is a statistically significant effect of the provenance latitude on the length of seedlings. The effect of altitude is slightly smaller, while the longitude of the provenance location has the smallest effect on the studied property. The study of the variability of Douglas-fir provenances in their juvenile development, as seedlings, is essential for reliable planning and implementation of further tests within pilot projects on allochthonous sites in Serbia.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".