Optic nerve hemangioblastomas – a review of visual outcomes
Bibliographic record
Abstract
halos around objects as well as headaches.His visual acuity was 20/60 in the left eye and 20/20 in the right eye and visual field testing revealed concentric narrowing.Fundoscopic examination revealed left primary optic atrophy.Endocrine examination was normal.The magnetic resonance imaging (MRI) (Figure 1A-D) showed a 1.8 cm extra-axial, well-defined, slightly lobulated lesion adjacent to the left anterior clinoid process and planum sphenoidale, compressing the optic nerve and the chiasm.The anterior cerebral artery (A1) was abutting the posterior surface of the tumor but was not encased.Most of the tumor was hypointense on T1-weighted images, enhanced uniformly, and showed heterogeneous intensity on T2weighted images.There was a small cystic component to the tumor postero-inferiorly.The tumor did not have an obvious dural attachment and a dural-tail could not be identified.It was clearly separate from the pituitary gland and pituitary stalk.There was compression of the left optic nerve with no clear plane of separation.Likewise there was edema along the optic tracts bilaterally, more so on the left side.The preoperative
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".