DARK, BITTER-TASTING NECTAR FUNCTIONS AS A FILTER OF FLOWER VISITORS IN A BIRD-POLLINATED PLANT
Bibliographic record
Abstract
Floral nectar is offered by plants to animals as a reward for pollination. While nectar is typically a clear liquid containing sugar and trace amounts of amino acids, colored nectar has evolved in several plant families. Here we explore the functional significance of the phenolic compounds that impart a dark brown color to the nectar of the South African succulent shrub Aloe vryheidensis. Flowers of this aloe are visited for their nectar by a suite of short-billed birds that are occasional nectarivores, including bulbuls, white-eyes, rock thrushes, and chats. Dark-capped Bulbuls were more likely to probe model flowers containing dark nectar than those containing clear nectar, suggesting a potential signaling function for dark nectar. However, the main effect of the phenolics appears to be to repel "unwanted" nectarivores that find their bitter taste unpalatable. Nectar-feeding honey bees and sunbirds are morphologically mismatched for pollinating A. vryheidensis flowers and strongly reject its nectar. However, the frugivorous and insectivorous birds that effectively pollinate this aloe are seemingly unaffected by the nectar's bitter taste. Thus the dark phenolic component of the nectar appears to function as a floral filter by attracting some animals visually and deterring others by its taste.
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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".