Variability of the width of Douglas-fir (Pseudotsuga menziessii /Mirb./Franco) needles in provenance tests
Bibliographic record
Abstract
Introduced tree species which have a wide natural range of distribution should be tested in experiments with different provenances. Douglas-fir is a very productive conifer species in its natural forest stands of America and Canada. Because of its high value, it is very popular in the countries of Europe and New Zealand as a conifer species suitable for reforestation. Its genetics and ecological adaptability can be confirmed by the investigations of its variable morphological traits, which is the aim of this research. Needle characteristics and needle morphology play a very important role in the performance of plant functions. Needle structure has a great influence on the plant life-cycle and their resistance to water loss, temperature and CO2 levels. The characteristics and morphology of needles were studied in order to determine whether there are differences between the provenances. Two experimental plots with twenty Douglas-fir provenances originally from North America were established in Serbia. A two-way analysis of variance was aimed at a closer study of the effects of the interaction of the site conditions of Douglas-fir provenances in the test locations in Serbia on the morphological traits of the needles.
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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 | 0.001 | 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) | 0.001 | 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".