Interactions between influences of genotype and grass competition on growth and wood stiffness of juvenile radiata pine in a summer-dry environment
Bibliographic record
Abstract
Clones of radiata pine (Pinus radiata D. Don) were established in two experiments on two contrasting pasture sites in Canterbury, New Zealand, with four levels of competition from grass as main plots within each experiment. Control was extended over the first 5 years at one site, whereas grass at the other site was controlled by a single herbicidal spray immediately after planting. At the latter site, 1 m diameter spots cleared with herbicide were compared with the same size spot created using a woven mat. Grass competition added up to 3 years to a rotation, and the gain from control was correlated with spot size. Competition control was most critical during the first year after planting. Trees grown within spots cleared by mats grew more slowly than those in weed-free spots cleared with herbicide. Green dynamic modulus of elasticity was related to genotype and increased with both slenderness and higher levels of pruning. Significant interactions between genotype and level of competition were observed for growth, indicating that choice of genotype can be a useful way of coping with pasture competition if managers wish to reduce the use of herbicides.
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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 | 0.001 |
| 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".