Mainly high phenotypic stability of black spruce clones for growth and wood traits in contrasted environments within the current breeding zones and multitrait selection in Québec's seed and breeding zones
Bibliographic record
Abstract
Selected trees from various progeny trials cannot be directly compared. As parents of clonal seed orchards and components of the next breeding cycle, it is crucial to verify their stability in different soil and climatic conditions and to rank them for multiple traits. A subset of the best trees selected for height at 10 or 15 years was cloned to establish 2 clone trials per population for 4 breeding populations, covering different bioclimatic domains of Québec. Between 80 and 119 clones per population were compared for height, diameter at breast height, indirect measure of wood density (Pilodyn 6J Forest device) and acoustic velocity (Fiber-gen Hitman ST300). Linear mixed models were used to estimate various genetic parameters, including genotypic values, using the Best Linear Unbiased Prediction (BLUP) method. With the genotypic values at 15 or 16 years for acoustic velocity and height, a selection index was calculated for ranking the clones. Clonal variances are significant for all growth and wood traits. Clonal heritabilities are low for growth traits with 1 exception (0.11-0.30) and range mainly from moderate to high for wood traits (0.29-0.70). Genotype × environment (G × E) interactions for growth traits are low for 2 populations (0.87-1) and mainly moderate for the 2 others (0.53-0.92). For wood traits, G × E interactions are low to almost nil and are mostly moderate for 1 population (0.69-1). In general, clones exhibit high stability (2 BLUP-based stability indexes) for growth and wood traits in contrasting soil and climatic conditions, except for the growth traits of 2 populations.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".