Current and Predicted Future Winter Warm Spells Would Affect Douglas Fir (Pseudotsuga menziesii (Mirb.), Franco) Seeds in the Early Stage of Germination More Than in the Late Stage of Germination
Bibliographic record
Abstract
Most tree species in the temperate climatic zone (including Douglas fir) disperse seeds in autumn. Some of them must be exposed to cold (0–10 °C) and moist conditions (cold stratification) to overcome dormancy and trigger germination. In the Northern Hemisphere, winter warm spells occur more frequently and last longer than in recent decades from eastern Canada to Europe. Our main research objective was to investigate the influence of current (1 or 3 days at day/night temperatures: 15 °C/10 °C) and future predicted (5 days at day/night temperatures: 25 °C/15 °C) winter warm spells on dormancy breaking and germination traits (germination energy—GE; germination capacity—GC; final germination capacity—FGC) of Douglas fir seeds from four old-growth stands in northern Poland. For this purpose, we interrupted cold stratification of seeds at different time points, i.e., after 3 weeks; 6 weeks; 9 or 3 weeks and 6 weeks; 3 and 9 weeks; 6 and 9 weeks; 3 and 6 weeks and 9 weeks. We found that for GE and GC, all main effects (populations—P; days of warm spell—D; stratification duration—W) and interactions were significant (except interaction P×D). FGC was significantly affected by the effects P and D and interactions of D × W and P × D × W. In addition, we found that the predicted warm spells negatively affected the early germination stage (GE and GC) of Douglas fir, but both current and future predicted winter conditions will not negatively affect the late germination stage (FGC).
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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 | 0.000 | 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".