Histological Investigation of Resected Dura Mater Attached to Spinal Meningioma
Bibliographic record
Abstract
In Brief Study Design. Histological observational study of patients with spinal meningioma. Objective. To clarify the status of tumor cell invasion into the dura mater and to provide fundamental information for appropriate management of dural attachment. Summary of Background Data. Histological appearance of the dura attached to spinal meningioma has not been sufficiently evaluated. Methods. Dura mater resected in a Simpson Grade 1 manner from 25 consecutive patients with spinal meningiomas (World Health Organization grade 1) was histologically observed to determine the status of tumor cell invasion. As no clear borders such as a tumor capsule between tumor and dura mater were observed, histological findings of the dura mater were classified into the following 3 categories: grade 1, no dural invasion, with only inflammation of the dura; grade 2: dural invasion below the zone between the inner and outer layers; and grade 3, dural invasion into or over the zone between the inner and outer layers (full-thickness invasion). Results. In our microscopic study, 19 of the 25 cases of spinal meningioma showed evidence of dural invasion and 15 cases showed full-thickness invasion. Conclusion. This histological investigation of resected dura mater attached to spinal meningioma showed a high rate of full-thickness tumor invasion into the dura mater. Dura mater resected in a Simpson Grade I manner from 25 consecutive patients with spinal meningiomas was histologically observed to determine the status of tumor cell invasion. Nineteen of the 25 cases of spinal meningioma showed evidence of dural invasion, and 15 cases showed full-thickness invasion.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".