Regulation of the mutualism between yuccas and yucca moths: intrinsic and extrinsic patterns of fruit set
Bibliographic record
Abstract
In plants that produce many more flowers than fruit, nonrandom patterns of fruit set arise from (1) factors intrinsic to inflorescence architecture, such as flower position or timing in the blooming sequence, and (2) factors extrinsic to the plant, such as pollinator visitation patterns. Here, we address how intrinsic and extrinsic factors drive fruit set in the interaction between Yucca kanabensis McKelvey and its pollinating moths. On inflorescences from which moths were excluded and all flowers were hand pollinated, the flowers most likely to produce fruit were (1) flowers from the first of three waves of flowering, (2) earlier opening flowers but not the earliest, and (3) flowers lower on the inflorescence but not the lowest. However, inflorescences experiencing natural levels of pollination and oviposition showed no effect of flowering wave, and flowers later in the flowering sequence and higher on the inflorescence were the ones most likely to produce fruit. The intrinsic patterns of fruit set were associated with differences among flowers, with the largest flowers being wave 1 flowers and flowers lower on the inflorescence. However, these differences among flowers did not translate into commensurate differences among fruit.Key words: mutualism, abscission, fruit, yucca, yucca moth.
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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 | 0.001 |
| 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".