Genetic parameter estimates for growth traits of black spruce in northwestern Ontario
Bibliographic record
Abstract
Genetic parameters of growth traits were estimated for first-generation selections of black spruce ( Picea mariana (Mill.) BSP) in northwestern Ontario from 720 open-pollinated families and more than 42 000 trees. Unbiased estimates of narrow-sense heritability for tree height growth averaged 0.19, 0.18, and 0.14 at ages 6, 11, and 19 years, respectively, from combined-site analyses compared with 0.25, 0.23, and 0.16 for the same ages from single-site analyses. Heritability estimates for diameter at breast height and stem volume were lower than that of height at age 19, suggesting that tree height is a more desirable trait for selection in black spruce. The moderately high estimates of type B genetic correlations implied limited operational importance of genotype × environment interactions. Estimates of age–age genetic correlation were high (>0.88) among cumulative tree height growth at 6, 11, and 19 years but lower between height increments from different age intervals. Estimates of type B age–age genetic correlation were more than 0.2 lower than their type A counterparts, suggesting strong effects of common environments on the estimates of type A genetic correlations. Based on the relative selection efficiencies, selection on cumulative tree height between ages 6 and 11 was more efficient than at age 19.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".