Comparison of the Retinal Structure and Function in Four Bird Species as a Function of the Time They Start Singing in the Morning
Bibliographic record
Abstract
We postulated that the retinas of bird species that are the earlier singers are more sensitive to low light conditions than species that sing closer to sunrise. The selected species were the American Robin (Turdus migratorius) and the Hermit Thrush (Catharus guttatus) as early singers, the Common Grackle (Quiscalus quiscula) and the Mourning Dove (Zenaida macroura) which join the dawn chorus near sunrise. Scotopic electroretinogram (ERGs) intensity-response functions were obtained from anesthetized birds, following which the animals were euthanized and their retinas processed for histological analysis. Based on k values, generally considered an adequate measurement of the scotopic (rod) retinal sensitivity, all species yielded comparable night vision capabilities. However, based on the maximal (mixed rod-cone response) amplitude of the scotopic b-wave, our results indicate that robins and thrushes yield larger scotopic ERGs compared with doves and grackles, but unexpectedly do not have higher rod:cone ratios. Increased thickness of the retinal inner nuclear layer and higher numbers of ganglion cells in robins and thrushes compared with doves and grackles suggest a greater number of synaptic connections maximizing vision under low light conditions, and might support their higher retinal responses under scotopic conditions. The higher ERG V(max) of robins and thrushes might also be explained, at least in part, by the optics (i.e., their lower minimum F-numbers), resulting in brighter retinal images, rather than from higher sensitivity of their retina. Our results suggest that an early onset of dawn singing might be correlated with the retinal ability to detect the first dim crepuscular lights.
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 | 0.001 | 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".