Comparison of Growth Performance and Stem Straightness among 23 Provenances of Quercus rubra Linne
Bibliographic record
Abstract
In order to select suitable Quercus tree, Quercus rubra L. was introduced from the native habitats in 1972 to conduct the adaptability test and showed an excellent result in growth performance and wood quality with outstanding adaptability, then the additional 23 provenances were introduced from Canada and USA in 1991 to conduct the provenance test in small scale with 75 trees per provenance.The growth performance of 23 provences were measured at age 4, 8, 10, 12 and 18 years, respectively.The result was that those Quercus rubra L. from New York State and Vermont State were excellent in height-growth, while those from Minnesota State and Virginia State showed poor growth performance.Similar results like in height-growth came out in diameter growth as well; especially those from Minnesota State and Virginia State showed poor growth performance not only in height and but also in diameter, while those from Illinois State and Vermont State showed excellent growth performance in diameter holding a high rank in height-growth.In the investigation of stem straightness according to the characteristic shape of tree trunk, the best provenance was the Beloeill provenance of Quebec Province in Canada, while the worst one was the Sauk Country provenance of Wisconsin State.Especially, the best Beloeill provenance of Quebec Province showed about 3.5 times superior features to our local species of Quercus acutissima, control.The Beloeill provenance is excellent in stem straightness and growth performance comparing to other provenances, which is considered as well adaptive to our climate and environment here in Korea.In addition, the investigation of growth performance and stem straightness showed that the excellent candidates were those Quercus rubra L. from New York State in USA and Quebec Province in Canada, located between 43 and 46 degrees northern latitude.Therefore, Quercus rubra L. is excellent in growth performance comparing to the local species of Quercus acutissima, and has a better adaptability than Quercus robur or Quercus alba, which is expected as the potential species to become our provenance resources and considered to be useful resources adaptable to those areas in South Korea.
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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 | 0.000 | 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".