Hybrid resection of a giant thigh plexiform neurofibroma
Bibliographic record
Abstract
PRESENTATION OF CASE: Authors present a case of a 55 year old patient with Type 1 neurofibromatosis (NF1) and a very large right thigh plexiform neurofibroma. The patient had increasing difficulty with mobilization due to this enlarging bulky mass. Preoperative embolization reduced the bleeding risk at surgery allowing successful gross resection of the mass by a multidisciplinary surgical team. Limb function was restored to normal. DISCUSSION: Massive plexiform neurofibromatosis is a rare expression of von Recklinghausen's disease or NF1. These large masses result in severe disfigurement and significant functional disability. They are extremely vascular and there is potential for malignant transformation. CONCLUSION: These massive tumors require complex preoperative, intraoperative and postoperative management strategies with involvement from a multidisplinary team. We discuss the challenges of surgical intervention and to discuss the current literature.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".