Douglas-fir provenance phenology observations
Bibliographic record
Abstract
Abstract Lavadinović V., Isajev V., Rakonjac L., Popović V., Lučić A.: Douglas-fir provenance phenology observations. Ekologia (Bratislava), Vol. 32, No. 4, p. 376-382, 2013. Introduction of species involves adaptation, productivity and success in new types of environmental conditions. The introduction also includes confirmation to bring in only species which are superior on their natural habitat. In Canada and western North America, Douglas fir (Pseudotsuga menziesii/Mirb./Franco) is one of the most ecologically and economically value trees. In Europe, New Zealand, Australia and Chile, Douglas fir is important as an exotic fast-growing timber species. Douglas fir has one of the widest natural ranges of any tree species, extending from the Pacific Coast to the eastern slope of the Rocky Mountains and from 19°N in Mexico to 55°N in western Canada. In Serbia, from the original seeds introduced from British Columbia and Canada, the experimental Douglas-fir provenance is established in a few locations. One of the main dangers for the Douglas fir is its sensitivity to the occurrence of late frost in spring and early occurrence of frost in the autumn. The aim of the paper is to test the effect of environment on the expression of Douglas-fir seed transfer. Bud burst phenology is closely related to genecology of introduced species. Douglas fir is susceptible to cold climate and most of its genetic structure and ability depends on its ecological adaptability. In order to avoid errors introduction of Douglas-fir provenances that are sensitive to the occurrence of extreme temperature, applied are researching for buds phenological changes Douglas fir, as an introduced species, has to be tested at the provenance level before its introduction to the new 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.001 |
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".