Sclerosing peritonitis associated with gynecological tumors: IgG4 peritoneal disease or a low grade spindle cell neoplasm?
Bibliographic record
Abstract
Sclerosing peritonitis is a fibro-inflammatory condition of the peritoneum which is rarely associated with ovarian neoplasia e.g., thecoma. The etiology is largely unknown. To investigate whether sclerosing peritonitis associated with gynecological neoplasia is a reactive process and part of the spectrum of IgG4-related disease, or a neoplastic process and harboring molecular alterations known to occur in low-grade spindle cell neoplasms. Six cases of sclerosing peritonitis and ovarian neoplasia were identified from the consultation files. Pathology materials were reviewed and select sclerosing peritonitis sections were stained with IgG and IgG4 immunohistochemical markers. Formalin-fixed paraffin-embedded tissue samples underwent RNA-sequencing using the Illumina TruSight RNA fusion assay. No case had an IgG:IgG4 positive ratio of >40% or met the additional criteria necessary to diagnose an IgG4-related disease. No characteristic spindle cell neoplasia -associated gene-fusions or chromosomal rearrangements, such as translocations or deletions, were identified on the sequencing platform. Our investigations do not support an IgG4-related disease or low grade spindle cell neoplasia as the etiology of the sclerosing peritonitis associated with ovarian neoplasia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".