Giant Cauda Equina Schwannoma
Bibliographic record
Abstract
STUDY DESIGN: Case report. OBJECTIVES: To present a rare case of a giant schwannoma of the cauda equina. SUMMARY OF BACKGROUND DATA: Giant spinal schwannoma of the cauda equina, which involves many nerve roots, is rare and there is usually no ossification in the schwannoma. It is unknown whether or not complete excision is preferable if the tumor is located in the lumbar lesion. METHODS: A 57-year-old woman had a 10-year history of low back pain. Scalloping of the posterior surface of the vertebral bodies from L3 to the sacrum was found. Magnetic resonance imaging disclosed a giant cauda equina tumor with multiple cysts. Central ossification revealed by computed tomography and an unusual myelogram made the preoperative diagnosis difficult. RESULTS: The patient underwent incomplete removal of the tumor, decompression of cysts, and spinal reconstruction. The tumor was proved to be a schwannoma. The postoperative course was uneventful and she has been almost free from low back pain for 3 years and 4 months. CONCLUSIONS: Giant schwannoma in the lumbar spine region is usually excised incompletely, because complete removal had the risk of sacrificing many nerve roots. In spite of the incomplete removal of the tumor, the risk of recurrence is low.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".