Functional differentiation in pollination processes between the outer and inner perianths in <i>Iris gracilipes</i> (Iridaceae)
Bibliographic record
Abstract
We examined the functional differentiation in pollination processes between the outer and inner perianths in Iris gracilipes A. Gray flowers. We manipulated the length of the outer and inner perianths and examined the effect on the following: number of pollinator approaches to, and landings on, flowers; pollen removal and deposition during a single pollinator visit; total number of pollen grains removed; and seed production. The outer perianths contributed to the functions of pollinator approach and landing, pollen removal, and seed production, but not to mechanical fitting of pollinators. Since flowers with shortened outer perianths gained less pollination success than control flowers, and since lengthening of outer perianths did not enhance pollination success, the length of the outer perianths might have evolved as an adaptive characteristic. On the other hand, the inner perianths contributed to the functions of pollinator approach and pollen removal but not to pollinator landing, mechanical fitting of pollinators, nor seed production. Since flowers with shortened inner perianths gained pollination success similar to that of control flowers, the adaptive length of the inner perianths may be shorter than what is found in present-day flowers. We propose that genetic correlation between the outer and the inner perianths might prevent shortening of the inner perianths.
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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".