Retinotopic organization of the visual cortex before and after decompression of the optic chiasm in a patient with pituitary macroadenoma
Bibliographic record
Abstract
Compression induced by a pituitary tumor on the optic chiasm can generate visual field deficits, yet it is unknown how this compression affects the retinotopic organization of the visual cortex. It is also not known how the effect of the tumor on the retinotopic organization of the visual cortex changes after decompression. The authors used functional MRI (fMRI) to map the retinotopic organization of the visual cortex in a 68-year-old right-handed woman before and 3 months after surgery for a recurrent pituitary macroadenoma. The authors demonstrated that longitudinal changes in visual field perimetry, as assessed by the automated Humphrey visual field test, correlated with longitudinal changes in fMRI activation in a retinotopic manner. In other words, after decompression of the optic chiasm, fMRI charted the recruitment of the visual cortex in a way that matched gains in visual field perimetry. On the basis of this case, the authors propose that fMRI can chart neural plasticity of the visual cortex on an individual basis and that it can also serve as a complementary tool in decision making with respect to management of patients with chiasmal compression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 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".