Leaf herbivory induces resistance against florivores in <i>Raphanus sativus</i>
Bibliographic record
Abstract
Florivory can have significant negative effects on plant fitness, driving selection for resistance traits in flowers. In particular, herbivory to leaves may induce resistance in flowers because herbivores on leaves often become florivores on flowers as plant ontogeny proceeds. The literature on inducible resistance in floral tissues is limited, so we used a series of experiments to determine whether prior leaf damage by Spodoptera exigua (Hübner) caterpillars affected florivore preference and performance on wild radish (Raphanus sativus L.). We found that Spodoptera exigua larvae preferred petals from control plants versus petals from plants exposed to prior leaf damage, and that larvae gained more mass on petals from control plants, although this depended on the presence of anthocyanins in the petals. Our results suggest that leaf damage can induce changes in petals that reduce Spodoptera exigua larval fitness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".