Bibliographic record
Abstract
Do fast-growing trees produce lower density wood? To determine the relationship between growth rate and wood density in plantation-grown aspen (Populus tremuloides Michx.), 199 trees in 20 clones were sampled from a 15-year-old clonal trial. This study found no evidence that fast-grown trees produce less dense wood. Phenotypic and genetic correlations between height, diameter, volume, and biomass were all high and significant. Wood density was not correlated with height or volume, but there were small and significant (p ≤ 0.05) positive phenotypic correlations with stem diameter. Genetic correlations between breast-height wood density and all three growth measures (height, DBH, and volume) were not significantly different from zero. This suggests that selection for growth will not influence wood density and vice versa. This paper discusses some possible reasons for the contradictions in the literature about the relationship between growth rate and wood density in aspen. The anatomy of juvenile or core wood is different from that of mature wood, and the relationship between density and growth rate also differs. The changing relative proportion of juvenile core wood with tree size may explain many of the apparent contradictions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".