PREDISPERSAL SEED HERBIVORES, NOT POLLINATORS, EXERT SELECTION ON FLORAL TRAITS VIA FEMALE FITNESS
Bibliographic record
Abstract
Herbivores that oviposit in flowers of animal-pollinated plants depend on pollinators for seed production and are therefore expected to choose flowers that attract pollinators. This provides a mechanism by which seed herbivores and pollinators could impose conflicting selection on floral traits. We measured phenotypic selection on floral traits of Lobelia siphilitica (Lobeliaceae) via female fitness to determine the relative strength of selection by pollinators and a specialist predispersal seed herbivore. We were able to attribute selection on flowering phenology to the herbivores. However, no selection could be attributed to pollinators, resulting in no conflicting selection on floral traits. Unlike pollinators, whose preference for certain floral traits does not always translate into higher fitness, any discrimination by seed herbivores is likely to decrease fitness of the preferred floral phenotype. Thus predispersal seed herbivores may be a significant agent of selection on floral traits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".