Data from: Pollination, mating and reproductive fitness in a plant population with bimodal floral-tube length
Bibliographic record
Abstract
Mating patterns and natural selection play important roles in determining whether genetic polymorphisms are maintained or lost. Here, we document an atypical population of Lapeirousia anceps (Iridaceae) with a bimodal distribution of floral-tube length and investigate the reproductive mechanisms associated with this pattern of variation. Flowers were visited exclusively by the long-proboscid fly Moegistorhynchus longirostris (Nemestrinidae), which exhibited a unimodal distribution of proboscis length and displayed a preference for long-tubed phenotypes. Despite being visited by a single pollinator species, allozyme markers revealed significant genetic differentiation between open-pollinated progeny of long- and short-tubed phenotypes suggesting mating barriers between them. We obtained direct evidence for mating barriers between the floral-tube phenotypes through observations of pollinator foraging, controlled hand pollinations and measurements of pollen competition and seed set. Intermediate tube-length phenotypes produced fewer seeds in the field than either long- or short-tubed phenotypes. Although floral-tube length bimodality may not be a stable state over long timescales, reproductive barriers to mating and low ‘hybrid’ fitness have the potential to contribute to the maintenance of this state in the short term.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.015 |
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".