Underwater linear polarization: physical limitations to biological functions
Bibliographic record
Abstract
Polarization sensitivity is documented in a range of marine animals. The variety of tasks for which animals can use this sensitivity, and the range over which they do so, are confined by the visual systems of these animals and by the propagation of the polarization information in the aquatic environment. We examine the environmental physical constraints in an attempt to reveal the depth, range and other limitations to the use of polarization sensitivity by marine animals. In clear oceanic waters, navigation that is based on the polarization pattern of the sky appears to be limited to shallow waters, while solar-based navigation is possible down to 200-400 m. When combined with intensity difference, polarization sensitivity allows an increase in target detection range by 70-80% with an upper limit of 15 m for large-eyed animals. This distance will be significantly smaller for small animals, such as plankton, and in turbid waters. Polarization-contrast detection, which is relevant to object detection and communication, is strongly affected by water conditions and in clear waters its range limit may reach 15 m as well. We show that polarization sensitivity may also serve for target distance estimation, when examining point source bioluminescent objects in the photic mesopelagic depth range.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".