Bibliographic record
Abstract
BACKGROUND: The primary pathophysiological feature of glaucoma is a progressive optic neuropathy with characteristic morphological changes of the optic disc and risk factors of age and intraocular pressure. Recently, involvement of other areas of the central nervous system (CNS) beyond the optic nerve has been demonstrated. This article addresses the proposition that glaucoma shares mechanistic and pathophysiologic features with neurodegenerations in the CNS. METHODS: The literature on CNS alterations in patients with glaucoma is reviewed with particular focus on neuroimaging and pathological studies. A theoretical framework for assessing whether glaucoma is truly a neurodegenerative disease is developed based on the comparison with neurodegenerative and nonneurodegenerative diseases. RESULTS: Although there is convincing evidence of abnormalities in CNS regions distal to the optic nerve in glaucoma, these are similar to those seen in other disorders of the proximal visual pathways, such as other optic neuropathies or retinal diseases. Similarly, features of glaucoma that are similar to neurodegenerations are also seen in nonneurodegenerative diseases. CONCLUSIONS: Glaucoma is less likely a primary neurodegeneration affecting the CNS and more likely a primary optic neuropathy with secondary effects in the CNS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".