Effects of Floral Scent, Color and Pollen on Foraging Decisions and Oocyte Development of Common Green Bottle Flies
Bibliographic record
Abstract
The common green bottle fly Lucilia sericata (Meigen) and other filth flies frequently visit pollen-rich composite flowers such as the Oxeye daisy, Leucanthemum vulgare Lam. In laboratory experiments with L. sericata, we investigated the effect of generic floral scent and color cues, and of Oxeye daisy-specific cues, on foraging decisions by recently eclosed flies. We also tested the effect of a floral pollen diet with 0-35% moisture content on the ability of females to mature their oocytes. Our data indicate that (1) young flies in the presence of generic floral scent respond more strongly to a uniformly yellow cue than to any other uniform color cue (green, white, black, blue, red) except for ultraviolet (UV); (2) the floral scent of Oxeye daisies enhances the attractiveness of a yellow cue; and (3) moisture-rich pollen provides nutrients that facilitate ovary maturation of flies. With evidence that L. sericata exploits floral cues during foraging, and that pollen can be an alternate protein source to animal feces and carrion, Pollen apparently plays a major role in the foraging ecology of L. sericata and possibly other filth flies. These flies, in turn, may play a significant role as pollinators, as supported by a recently published study.
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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".