Estimating of Additive, Dominance, and Epistatic Genetic Variance in Eucalypt Hybrid Population
Bibliographic record
Abstract
Abstract Additive, dominance and epistasis genetic variances were estimated from analysis of a clonally replicated full-sib progeny test grown in the Republic of Congo. Phenotypic variance components were estimated for ages 4 through 25 months for growth and at ages 8 and 18 months for ecophysiological traits. The estimation of genetics effects was derived from the individual mixed model. Genetic structure was incorporated into variances and covariance’s effects based on markers information. The detected genetic effects of epistasis are significant in some traits. This study shows that epistasis variance can be non-zero and contribute significantly to the genetic variability of growth and ecophysiological traits. We conclude that the epistatic effect for quantitative traits may exist, but estimates may not be obtained, either because the models used are inappropriate or because the epistasis variance is too small relative to other components of the genetic variance to be estimated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".