Subclassification of Ovarian Surface Epithelial Tumors Based on Correlation of Histologic and Molecular Pathologic Data
Bibliographic record
Abstract
Surface epithelial tumors are a large and heterogeneous group of neoplasms that are subclassified based on cell type and malignant potential. The objective of this review is to examine the correlations between recent molecular pathology data and the traditional histopathologic classification of surface epithelial tumors. By doing so, 6 distinct subsets of ovarian epithelial neoplasia can be identified with potential treatment implications 1. high-grade serous, high-grade endometrioid, and undifferentiated carcinomas; 2. low-grade serous carcinomas and serous borderline tumors; 3. mucinous carcinomas and mucinous borderline tumors of intestinal type; 4. low-grade endometrioid carcinomas and endometrioid borderline tumors; 5. clear cell carcinomas; and 6. transitional cell carcinomas.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".