Changes in anatomical structure and cell wall composition during male inflorescence development of <i>Castanea mollissima</i>
Bibliographic record
Abstract
The Chinese chestnut ( Castanea mollissima Blume) is a dioecious plant in which the number of male inflorescences far exceeds that of female inflorescences. Therefore, it is of interest to study the differentiation of male flowers in C. mollissima. In this study, the male inflorescences of “Yanshanhongli” C. mollissima were observed. Then, the main components of the cell wall were stained by fluorescence and immunofluorescence labeling techniques to examine the changes in cell wall components. The results showed that the development of the male inflorescence of C. mollissima had different transverse elongation and longitudinal elongation. In addition, the development of male inflorescences and anthers were divided into five and four major stages, respectively, according to the microstructural changes. Immunostaining indicated that the fluorescence intensity of cellulose increased with the development of male inflorescences of C. mollissima. The fluorescence intensity of low-esterified homogalacturonan (HG) was stronger in the early stage, while the fluorescence intensity of high-esterified HG was stronger thereafter. This research provides new insights into the changes in cell wall components during the growth and development of male inflorescences of C. mollissima and important clues for exploring the growth and development mechanism of male inflorescences of C. mollissima.
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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 | 0.000 | 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".