Density and rectangularity of planting influence 20-year growth and development of red alder
Bibliographic record
Abstract
Red alder (Alnus rubra Bong.) seedlings were planted in northwestern Oregon, U.S.A., at five initial spacings: 0.6 × 1.2 m, 1.2 × 1.2 m, 1.2 × 1.8 m, 1.8 × 1.8 m, and 2.5 × 2.5 m. Up to about age 10, tree and stand characteristics were correlated primarily with initial planting density in the expected manner; through age 20, however, tree growth and stand development in plots planted at rectangular spacings were substantially more rapid than in the two closest square spacings. Mean stand diameter ranged from 19.2 cm in the widest spacing to 14.0 cm in the closest square (1.2 × 1.2 m) spacing; mean tree height decreased from nearly 24 m in the widest (2.5 × 2.5 m) spacing to about 18 m in the closest square spacing. Diameterdensity relationships in the widest spacing were consistent with existing density management guidelines, but very dense spacings and rectangular plantings began to experience substantial mortality at smaller diameters than assumed in the guidelines. We suggest that rectangular planting of red alder at dense spacing enhanced stand differentiation, accelerated competition-related mortality, and thus led to improved growth of surviving trees.
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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 | 0.000 | 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".