Bibliographic record
Abstract
PURPOSE OF REVIEW: Glaucoma is a leading cause of irreversible world vision loss characterized by progressive retinal ganglion cell death. Elevated eye pressure is a major risk factor for glaucoma; however, despite effective medical and surgical therapies to reduce intraocular pressure, progressive vision loss among glaucoma patients is common. These observations suggest that mechanisms independent of intraocular pressure are also implicated in glaucomatous degeneration. Numerous similarities exist between glaucoma and neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Similarities include the selective loss of neuron populations, transsynaptic degeneration in which disease spreads from injured neurons to connected neurons, and common mechanisms of cell injury and death. RECENT FINDINGS: Glaucomatous injury to retinal ganglion cells has profound effects on target vision structures within the brain, including the lateral geniculate nucleus and visual cortex in experimental primate and human glaucoma. Mechanisms involved in central visual system damage in glaucoma include oxidative injury and glutamate toxicity, as seen in neurodegenerative diseases. SUMMARY: Glaucoma as a neurodegenerative disease is a valid working hypothesis to understand neural injury in the visual system. This paradigm may stimulate the discovery of innovative intraocular pressure-independent strategies to help prevent loss of vision in glaucoma patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".