Establishment and growth in seedlings of<i>Fagus sylvatica</i>and<i>Quercus robur</i>: influence of interference from herbaceous vegetation
Bibliographic record
Abstract
The interference from natural vegetation on the establishment and growth in Fagus sylvatica L. and Quercus robur L. was studied on an open site starting from bare soil. Four treatments were applied: herbicide, herbicide plus fertilization, mowing, and untreated control. Seedlings of beech and oak were spring planted side-by-side in two subsequent years and monitored through the 1995, 1996, and 1997 growing seasons. Interference had a strong negative influence on the seedling shoot dry mass, leaf area, relative diameter growth, leaf nitrogen concentration, and leaf water potential and conductance. Oak had a shorter period of transplanting shock, a higher relative growth rate during interference from vegetation, and deeper roots than beech. Therefore, oak is more easily established than beech, which initially may need more intense site preparation. Neither fertilization compared with vegetation control only, nor mowing compared with untreated control, influenced seedling growth. Low soil water potential had a strong influence on seedling growth, although the competing vegetation at the same time reduced light, soil temperature, and the soil nitrogen concentration.
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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".