Mammal pollinators lured by the scent of a parasitic plant
Bibliographic record
Abstract
To communicate with animals, plants use signals that are distinct from their surroundings. Animals generally learn to use these signals through associative conditioning; however, signals are most effective when they elicit innate behavioural responses. Many plant species have flowers specialized for pollination by ground-dwelling mammals, but the signals used to attract these pollinators have not been elucidated. Here, we demonstrate the chemical basis for attraction of mammal pollinators to flowers of the dioecious parasitic plant Cytinus visseri (Cytinaceae). Two aliphatic ketones dominate the scent of this species; 3-hexanone, which elicits strong innate attraction in rodents, and 1-hexen-3-one, which repels them in isolation, but not in combination with 3-hexanone. The aliphatic ketone-dominated scent of C. visseri contrasts with those of insect-pollinated plants, which are typically dominated by terpenoids, aromatic or non-ketone aliphatic compounds. 3-hexanone is also known from some bat-pollinated species, suggesting independent evolution of plant signals in derived, highly specialized mammal-pollination systems.
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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) | 0.002 | 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".