Visual specialization of an herbivore prey species, the white-tailed deer
Bibliographic record
Abstract
To gain knowledge of visual specializations influencing the behavior of white-tailed deer ( Odocoileus virginianus (Zimmermann, 1780)), we examined gross eye characteristics, structural organization of the retina, and the density and distribution of cone photoreceptors. White-tailed deer possess ocular features similar to other ungulates including a horizontal slit pupil, reflective tapetum lucidum, typical retinal structure, and medium wavelength sensitive cone photoreceptors concentrated in a horizontal visual streak. The tapetum was found to cover the superior portion of the eye and overlapped the horizontal visual streak. Comparisons between fawns and adults did not reveal any differences in retinal thickness, retinal nuclei counts, or cone photoreceptor counts. While M-cones had increased density in the visual streak, S-cones were distributed evenly across the entire retina. Schematic eye calculations of a 0.5-year-old deer indicated a hyperopic eye (+7.96) with a F/# ranging from 5.55 to 1.39 for pupil diameters of 3 to 12 mm. As expected for a crepuscularly active prey species, the visual system of white-tailed deer is specialized for sensitivity in low-light conditions and detection of predators.
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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 | 0.000 | 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".