Skull Base Inverted Papilloma: A Comprehensive Review
Bibliographic record
Abstract
Skull base inverted papilloma (IP) is an unusual entity for many neurosurgeons. IP is renowned for its high rate of recurrence, its ability to cause local destruction, and its association with malignancy. This paper is a comprehensive review of the reports, studies, and reviews published in the current biomedical literature from 1947 to September 2010 and synthesize this information to focus on its potential invasion to the base of the skull and possible intradural extension. The objective is to familiarize the clinician with the different aspects of this unusual disease. The role of modern diagnostic tools in medical imaging in order to assess clearly the limits of the tumors and to enhance the efficiency and the safety in the choice of a surgical approach is pointed out. The treatment guidelines for IP have undergone a complex evolution that continues today. Radical excision of the tumour is technically difficult and often incomplete. Successful management of IP requires resection of the affected mucosa which could be achieved with open surgery, endoscopic, or combined approach. Radio and chemotherapy were used for certain indications. More optimally research would be a multicenter randomized trials with large size cohorts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".