Effects of the number of embryos in a seed and seed mass on seedling survival and growth in polyembryonic <i>Ophiopogon japonicus</i> var. <i>umbrosus</i> (Asparagaceae)
Bibliographic record
Abstract
Research on polyembryony suggests that the presence of multiple embryos in a seed confers an advantage for seedling survival. Because observations from embryo to seedling stages are lacking, however, the effect of the exact number of embryos on seedling survival is unclear. In this study, we evaluated the effect of seed embryo number on seedling survival and growth to determine the number of embryos in a seed that are advantageous for seedling survival in Ophiopogon japonicus (Thunb.) Ker Gawl. var. umbrosus Maxim., which is a taxon exhibiting cleavage polyembryony. We also investigated whether seed mass affects seed embryo number and seedling survival and growth. We found that the number of embryos in seeds of O. japonicus var. umbrosus was weakly dependent on seed mass. As the number of embryos increased, the number of seedlings surviving from seeds initially increased and then decreased; the greatest number of seedlings was produced from an intermediate number of embryos, with the number of embryos producing the greatest number of seedlings increasing with seed mass. The sum of individual seedling lengths increased with the number of seedlings. Our results indicate that an intermediate number of embryos may be advantageous in polyembryonic O. japonicus var. umbrosus.
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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".