Genetic Variation and Tree Improvement of Konishii fir (<i>Cunninghamia lanceolata</i>(Lamb.) Hook. var.<i>konishii</i>) in Taiwan
Bibliographic record
Abstract
Abstract We analyzed a 21-year old progeny test of Konishii fir (Cunninghamia lanceolata(Lamb.) Hook. var.konishii) involving 75 families. Tree height and diameter at breast height (DBH) were periodically recorded. At age 21, average height, DBH, and volume were 15.2 m, 20.2 cm, and 278 dm3, respectively. At this age, family accounted for 9, 12, and 11% of the total variance in height, DBH and volume, respectively. Also at age 21, individual tree heritability was 0.35, 0.49, and 0.45 for height, DBH and volume, respectively, and family heritability was 0.53, 0.69, and 0.66 for the three respective characteristics. The age trend for all genetic parameters was more stable for DBH than for height and volume. Family (backward) selection for DBH at age 21 resulted in a 9.6% gain and indirectly 5.1 and 21.0% gains for height and volume, respectively, compared to 5.2 and 20.1% gains for height and volume, respectively, when selection for these characteristics is done directly. DBH is an effective proxy trait for selection in growth. DBH is also less susceptible than height to typhoon damage, which frequently afflicts tree plantations in Taiwan. Therefore, DBH should be considered as the primary trait for selection for Konishii fir in Taiwan. Konishii fir is a genetically variable species despite its limited geographic range, and is fast growing which makes it a viable candidate species for tree improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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 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".