Predicted genetic gains and testing efficiency from two loblolly pine clonal trials
Bibliographic record
Abstract
Clonal field trials were established at two sites using rooted cuttings from 450 clones of eight full-sib families of loblolly pine (Pinus taeda L.). Height, survival, fusiform rust infection (caused by Cronartium quercuum (Berk) Miyabe ex Shirai f.sp. fusiforme), bole straightness, and diameter were measured after four growing seasons. There were significant differences among full-sib families and among clones within families for all traits studied. Moderately high within-family repeatabilities of clone means (0.50 to 0.75) for growth traits and a very high within-family repeatability of clone means (0.94) for fusiform rust infection were estimated. When the best eight clones were selected regardless of family structure, the volume yield was 52% greater than that of the unimproved seedlings at two sites. Selection of the best two clones from each of four families produced only slightly lower estimated genetic gains than the above scenario. The probability of fusiform rust infection ranged from 0.08 to 0.93 among clones at the South Carolina site. Predicted genetic gain for rust resistance was relatively insensitive to selection intensity, as there were numerous clones with high apparent resistance. The number of ramets per clone necessary to reliably characterize performance on one site was estimated to be between four and six. These results contribute to estimates of the gains available from clonal forestry and will help guide clonal testing and selection programs. Implementation of clonal forestry and cost issues are discussed.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".