Gender effects on Salix suchowensis growth and wood properties as revealed by a full-sib pedigree
Bibliographic record
Abstract
Among dioecious plant species, it is common for the males to grow faster than the females. In this study, we investigated the effects of gender on the growth and wood properties of Salix suchowensis Cheng ex Zhu. using a full-sib pedigree. We observed that the segregation of sex followed a 1:1 ratio and that gender significantly affected growth traits, including tree height, ground diameter, and biomass production. Additionally, the females generally performed better than the males, which is in contrast to the common scenario for dioecious plant species. There is currently relatively little information regarding gender effects on wood properties. Therefore, we also measured the basic wood density and cellulose, hemicellulose, and lignin contents. We determined that any differences between the male and female trees regarding these wood property traits were insignificant. Recent studies revealed that the sex of willow trees is controlled by a ZW sex determination system in which the female is the heterogenic gender. Because female heterogamety is relatively rare in higher plants, our findings may be relevant for characterizing the gender effects on biological performance in dioecious plants regulated by the ZW sex determination system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".