Variation in opsin transcript expression explains intraretinal differences in spectral sensitivity of the northern anchovy
Bibliographic record
Abstract
Vertebrate retinal photoreceptors house visual pigments that absorb light to begin the process of vision. The light absorbed by a visual pigment depends on its two molecular components: protein (opsin) and chromophore (a vitamin A derivative). Although an increasing number of studies show intraretinal variability in visual pigment content, it is only for two mammals (human and mouse) and two birds (chicken and pigeon) that such variability has been demonstrated to underlie differences in spectral sensitivity of the animal. Here, we show that the spectral sensitivity of the northern anchovy varies with retinal quadrant and that this variability can be explained by differences in the expression of opsin transcripts. Retinal (vitamin A1) was the only chromophore detected in the retina, ruling out this molecular component as a source of variation in spectral sensitivity. Chromatic adaptation experiments further showed that the dorsal retina had the capacity to mediate color vision. Together with published results for the ventral retina, this study is the first to demonstrate that intraretinal opsin variability in a fish drives corresponding variation in the animal's spectral sensitivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".