Seed production in<i>Cardiocrium cordatum</i>: effects of nitrogen and dry mass availability of a plant
Bibliographic record
Abstract
To clarify how seed production depends on the relative N and dry mass availability, we examined the number and size of seeds, and the loss of dry mass in Cardiocrium cordatum (Thunb.) Makaino plants that differed naturally in overall size and stem N content. After adjusting for plant size (basal stem diameter was used as a criterion of plant size), the amount of dry mass lost because of respiration in a plant decreased with an increase in the stem N content of the plant, whereas the total dry mass of seeds of a plant increased with an increase in the stem N content. Plants with a high stem N content relative to dry mass status used dry mass resources more efficiently in seed production by reducing the loss of dry mass. Plants with a higher stem N content produced a greater number of seeds, and the amount of dry mass lost decreased with an increase in the number of seeds of the plant, possibly because the resources allocated to seed production are consumed rapidly, if numerous seeds simultaneously absorb those resources. However, the stem N content of a plant had no influence on the mean seed dry mass, seed N content, and the seed N concentration, and the latter three parameters did not affect respiration loss of dry mass. We concluded that plants undergoing seed production reduce dry mass loss if their relative N to dry mass availability is high, through an increase in the numbers of seeds they produce.
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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 | 0.001 |
| 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".