Bibliographic record
Abstract
Non-arteritic anterior ischemic optic neuropathy (NAION) is the most common cause of optic nerve swelling and optic neuropathy in adults over 50 years of age. Risk factors that have been strongly associated with NAION include hypertension, hypercholesterolemia, diabetes mellitus, cardio- and cerebrovascular disease, and obstructive sleep apnea. While the exact pathogenesis of a NAION has not been elucidated, the prevailing theory is that it is caused by hypoperfusion of the short posterior ciliary arteries supplying the optic nerve, which then causes ischemia which induces swelling of the portion of the optic nerve traveling through the small opening in a scleral canal. This, in turn, leads to the compartment syndrome involving neighboring axons that are now compressed in a space limited by the small opening in the scleral canal, leading to apoptosis and death of the ganglion cells whose axons comprise the optic nerve. The natural history of NAION has been elucidated in Ischemic Optic Neuropathy Decompression Trial which demonstrated that about 30% of patients would regain 3 or more lines of vision at 2 years follow up, 20% will lose 3 or more lines of vision and in the majority of patients, the vision will remain unchanged after the onset. In reality, visual acuity will not change in the vast majority of patients after the acute event has resolved, and the ones who are able to see a few lines better likely learned to improve their fixation.
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 | 0.000 | 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) | 0.007 | 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".