Shining a light on UV-fluorescent floral nectar after 50 years
Bibliographic record
Abstract
Nature is aglow with numerous captivating examples of UV-fluorescence in the animal kingdom. Despite a putative role as a visual signal, exploration of UV-fluorescence in plants and its role in plant-animal interactions is lagging in comparison. Almost 50 years ago, UV-fluorescence of floral nectar, a crucial reward for pollinators, was reported for 23 flowering plant species. Since this intriguing discovery, UV-fluorescent nectar has only seldom been addressed in the scientific literature and has not been scrutinized in a phylogenetic or ecological context. Here, we report the prevalence of vibrant UV-fluorescent floral nectar across the family Cleomaceae, including the first photographic documentation in vivo colour for flowering plants. Though Cleomaceae flowers are morphologically diverse varying in colour, nectary prominence, and nectar volume, UV-fluorescent floral nectar may be a ubiquitous characteristic of the family. Fluorescence spectra show that the identity and number of fluorescent compounds in floral nectar may differ among Cleomaceae species. As Cleomaceae pollinators range from insects to bats and birds, we suggest that the UV-fluorescent floral nectar not only functions as a visual cue for the diurnal pollinators but also for the nocturnal/crepuscular pollinators in low light settings.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".