Investigating mechanisms of polarized light sensitivity in the small white butterfly <i>Pieris rapae</i>
Bibliographic record
Abstract
Abstract There is an ever increasing number of arthropod taxa shown to have polarization sensitivity throughout their compound eyes. However, the mechanisms underlying arthropod perception of polarized reflections from objects such as plants are not well understood. The small white butterfly, Pieris rapae , has been demonstrated to exploit foliar polarized reflections, specifically the degree of linear polarization ( DoLP ), to recognize host plants. The well-described visual system of P. rapae includes several photoreceptor types (red, green, blue) that are sensitive to polarized light. Yet, the mechanism underlying the behavioral responses of P. rapae to stimuli with different DoLPs remains unknown. To investigate potential mechanisms, we designed several two-choice behavioral bioassays, displaying plant images on paired LCD monitors which allowed for independent control of polarization, color and intensity. We found that shifts in image intensity had a similar effect on P. rapae preferences for stimuli dissimilar in DoLP and dissimilar in color, suggesting DoLP differences are perceived as color. When a DoLP choice was offered between plant images manipulated in a manner to minimizing the response of blue, red, or blue and red photoreceptors, P. rapae shifted its preference for DoLP , suggesting a role for red, green and blue polarization-sensitive photoreceptors. Modeling of P. rapae photoreceptor responses to test stimuli suggests that differential DoLP is not perceived solely as a color difference. Our combined results suggest that P. rapae females process and interpret polarization reflections in a way different from that described for other polarization-sensitive taxa.
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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".