The Gateway to the Brain: Dissecting the Primate Eye
Bibliographic record
Abstract
The visual system in humans is considered the gateway to the world and plays a principal role in the plethora of sensory, perceptual and cognitive processes. It is therefore not surprising that quality of vision is tied to quality of life . Despite widespread clinical and basic research surrounding the causes of visual disorders, many forms of visual impairments, such as retinitis pigmentosa and macular degeneration, lack effective treatments. Non-human primates have the closest general features of eye development to that of humans. Not only do they have a similar vascular anatomy, but amongst other mammals, primates have the unique characteristic of having a region in the temporal retina specialized for high visual acuity, the fovea(1). Here we describe a general technique for dissecting the primate retina to provide tissue for retinal histology, immunohistochemistry, laser capture microdissection, as well as light and electron microscopy. With the extended use of the non-human primate as a translational model, our hope is that improved understanding of the retina will provide insights into effective approaches towards attenuating or reversing the negative impact of visual disorders on the quality of life of affected individuals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".