High genetic gains in growth and resistance to white pine weevil for the next Norway spruce breeding and propagation populations in Quebec, Canada
Bibliographic record
Abstract
Genetic parameters for growth (height, diameter, and volume) and resistance to the white pine weevil were estimated from 209 Norway spruce families aged 15 or 20 years old. Individual heritability values ranged from low to moderate, while family heritability values were moderate to high. This suggests that there is a genetic control for these variables. A selection index was developed to rank individuals on both volume growth and resistance to the white pine weevil. Opsel 2.0 software was used for selection to optimize genetic gain while keeping the level of relatedness between selected trees below an acceptable threshold. The selection of the best 70 individuals, i.e., the top 1% of the populations evaluated, resulted in volume gains of 15.5% and weevil resistance gains of 30.3% making it possible to create a new, more productive and weevil-resistant Norway spruce population. These new breeding and propagation populations will be planted in various locations in the province of Quebec and will be used for the operational deployment of this improved material.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| 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".