Genetic control and early selection of three <i>Corymbia</i> species
Bibliographic record
Abstract
The main objective of this study was to investigate genetic control for individual volume and genetic and phenotypic correlation between trait measured at two different ages. We also assessed three different selection intensities ( i = 1%, i = 5% and i = 10%) to understand the effects on genetic gain and effective size. Eight progeny tests were evaluated which included three tests of Corymbia citriodora subsp. citriodora (CCT), two tests of C. citriodora subsp. variegata (CCV), and three tests of C. torelliana (CTO). Narrow-sense heritability [Formula: see text] ranged from 0.26 to 0.62 for the CCT tests, from 0.07 to 0.21 for the CCV tests, and from 0.14 to 0.69 for CTO. The coefficients of individual genetic variation ([Formula: see text]) ranged from 22.5% to 63.9% for CCT, from 19.3% to 28.3% for CCV, and from 22.8% to 41.3% for CTO. Considering a selection intensity of 10%, the Ne after selection would range from 31 to 98 for CCT, 36 to 47 for CCV, and 45 to 62 for CTO. For the TP8 CTO test, a selection intensity greater than 10% is recommended. With a selection intensity of 10%, genetic gains ranged from 25 to 107% for CCT, from 14 to 27% for CCV, and from 19 to 64% for CTO.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".