Ovarian Surface Epithelium: Biology, Endocrinology, and Pathology*
Bibliographic record
Abstract
The epithelial ovarian carcinomas, which make up more than 85% of human ovarian cancer, arise in the ovarian surface epithelium (OSE). The etiology and early events in the progression of these carcinomas are among the least understood of all major human malignancies because there are no appropriate animal models, and because methods to culture OSE have become available only recently. The objective of this article is to review the cellular and molecular mechanisms that underlie the control of normal and neoplastic OSE cell growth, differentiation, and expression of indicators of neoplastic progression. We begin with a brief discussion of the development of OSE, from embryonic to the adult. The pathological and genetic changes of OSE during neoplastic progression are next summarized. The histological characteristics of OSE cells in culture are also described. Finally, the potential involvement of hormones, growth factors, and cytokines is discussed in terms of their contribution to our understanding of the physiology of normal OSE and ovarian cancer development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".