Polarized light sensitivity in <i>Pieris rapae</i> is dependent on both color and intensity
Bibliographic record
Abstract
There is an ever increasing number of arthropod taxa shown to have polarization sensitivity throughout their compound eyes. However, the downstream processing of polarized reflections from objects is 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 roles and interaction among photoreceptors underlying the behavioral responses of P. rapae to stimuli with different DoLPs remain unknown. To investigate potential neurological 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. When we presented choices between stimuli that differed in either color or DoLP, both decreasing and increasing the intensity of the more attractive stimulus reduced the strength of preference. This result suggests differences in color and DoLP are perceived in a similar manner. When we offered a DoLP choice between plant images manipulated to minimize the response of blue, red, or blue and red photoreceptors, P. rapae shifted its preference for DoLP, suggesting a role for all of these 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 | 0.001 |
| 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".