Efficiency of early selection for rotation-aged growth and wood density traits in <i>Pinus radiata</i>
Bibliographic record
Abstract
A total of 1097 cross-sectional wood disks from breast height were sampled from two rotation-aged (27 and 31 years from planting) genetic trials of radiata pine (Pinus radiata D. Don) in Australia to estimate the genetic correlation between early and rotation-aged growth and wood quality traits and the efficiency of early selection. Annual growth-ring width and density, diameter at breast height (DBH), and area-weighted density (AD) from 30 open-pollinated families were measured using X-ray densitometry. Genotype × site interactions were not significant for density and growth traits. Ring density increased steadily from the pith to cambial age 14, and then density had little change in the following years. For AD, the family and individual heritability estimates were about 0.60 and 0.30 after the first 2 years. For DBH, family and individual narrow-sense heritability estimates increased steadily after the first 4 years, and family heritability increased to 0.7 at a cambial age of 11 and had little change thereafter. Individual heritability estimate increased to 0.4 at cambial age 14 and was similar for the later ages. Beyond a cambial age of 5 years, there were strong negative genetic correlations of around 0.80 between AD and DBH. Ageage genetic correlations for AD were high and reached 0.80 and above after cambial age 3. Ageage genetic correlations for DBH were similar to AD, except the first two years. The most efficient early selection year was between ages 4 and 6 years after planting for AD, and between ages 8 and 11 years for DBH.
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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 | 0.001 | 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".