The role of wild rice (<i>Oryza rufipogon</i>) awns in seed dispersal
Bibliographic record
Abstract
Abstract Cultivated rice ( Oryza sativa L.) was domesticated from the Asian wild species O. rufipogon . Compared with cultivated rice, wild rice has spikelets/seeds with long barbed awns. In order to evaluate the role of awns in wild rice, four seed groups with different awn lengths (full, half, quarter and no awns) were prepared, and the following seed dispersal movements were investigated under simulated natural conditions as observed in the tropical Asian habitat: (1) seed detachment from the parent plant; (2) falling angle of mature seed; (3) ability to slip into small spaces; (4) horizontal movement on the ground and (5) horizontal movement in water. As a result, awns were found to enhance the detachment of matured seeds from the panicles in the initial seed dispersal step. They regulated vertical orientation in the air, and the vertical form may enable seeds to squeeze to the ground. The awned seeds also showed advantages in horizontal movements on the ground and in the water. In most of the experiments, seeds with full awns showed the best performance for seed dispersal, suggesting that wild rice keeps long awns to survive under natural conditions. Since seed awning is dominantly controlled by wild functional alleles at several loci, wild rice may be able to prevent a drastic reduction of awn length.
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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) | 0.000 | 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".