Meningioma with dural venous sinus invasion and jugular vein extension
Bibliographic record
Abstract
Meningiomas represent the most common benign intracranial neoplasm in adults, with a considerably lower incidence in children. The authors present the case of an intracranial meningioma with invasion of, and intraluminal extension into, the transverse and sigmoid sinuses, jugular bulb, and internal jugular vein, resulting in venous occlusion in a 14-year-old girl. Computed tomography scanning, MR imaging, and conventional angiography were performed preoperatively. The patient underwent a 2-stage resection: the supratentorial component was resected first, and the infratentorial and venous sinus and jugular vein components were subsequently removed using a combined skull base approach. Gross-total resection was achieved by opening the lateral dural sinus and removing the meningioma from within the transverse and sigmoid sinuses, the jugular bulb, and the internal jugular vein. The patient remained neurologically intact after the staged tumor resections. Postoperative imaging confirmed the gross-total resection. This case illustrates the unusual property of an intracranial meningioma to invade the intrasinusoidal space and extend into the jugular vein without adherence to the underlying venous endothelium of the jugular vein.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".