The molecular origin and evolution of dim-light vision in mammals
Bibliographic record
Abstract
The nocturnal origin of mammals is a longstanding hypothesis that is considered instrumental for the evolution of endothermy, a potential key innovation in this successful clade. This hypothesis is primarily based on indirect anatomical inference from fossils. Here, we reconstruct the evolutionary history of rhodopsin--the vertebrate visual pigment mediating the first step in phototransduction at low-light levels--via codon-based model tests for selection, combined with gene resurrection methods that allow for the study of ancient proteins. Rhodopsin coding sequences were reconstructed for three key nodes: Amniota, Mammalia, and Theria. When expressed in vitro, all sequences generated stable visual pigments with λMAX values similar to the well-studied bovine rhodopsin. Retinal release rates of mammalian and therian ancestral rhodopsins, measured via fluorescence spectroscopy, were significantly slower than those of the amniote ancestor, indicating altered molecular function possibly related to nocturnality. Positive selection along the therian branch suggests adaptive evolution in rhodopsin concurrent with therian ecological diversification events during the Mesozoic that allowed for an exploration of the environment at varying light levels.
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) | 0.000 | 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 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".