Do the fluorescent red eyes of the marine fish <i>Tripterygion delaisi</i> stand out? In situ and in vivo measurements at two depths
Bibliographic record
Abstract
Abstract Since the discovery of red fluorescence in fish, much effort has been invested to elucidate its potential functions, one of them being signaling. This implies that the combination of red fluorescence and reflection should generate a visible contrast against the background. Here, we present in vivo iris radiance measurements of Tripterygion delaisi under natural light conditions at 5 and 20 m depth. We also measured substrate radiance of shaded and exposed foraging sites at those depths. To assess the visual contrast of the red iris against these substrates, we used the receptor noise model for chromatic contrasts and Michelson contrast for achromatic calculations. At 20 m depth, T. delaisi iris radiance generated strong achromatic contrasts against substrate radiance, regardless of exposure, and despite substrate fluorescence. Given that downwelling light above 600 nm is negligible at this depth, we can attribute this effect to iris fluorescence. Contrasts were weaker in 5 m. Yet, the pooled radiance caused by red reflection and fluorescence still exceeded substrate radiance for all substrates under shaded conditions and all but Jania rubens and Padina pavonia under exposed conditions. Due to the negative effects of anesthesia on iris fluorescence, these estimates are conservative. We conclude that the requirements to create visual brightness contrasts are fulfilled for a wide range of conditions in the natural environment of T. delaisi .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".