Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ovarian epithelial cancer (OEC) accounts for 90% of all ovarian cancers and is the leading cause of death from gynecological cancers in North America and Europe. Despite its clinical significance, the factors that regulate the development and progression of ovarian cancer are among the least understood of all major human malignancies. The two gonadotropins, FSH and LH, are key regulators of ovarian cell functions, and the potential role of gonadotropins in the pathogenesis of ovarian cancer is suggested. Ovarian carcinomas have been found to express specific receptors for gonadotropins. The presence of gonadotropins in ovarian tumor fluid suggests the importance of these factors in the transformation and progression of ovarian cancers as well as being prognostic indicators. Functionally, there is evidence showing a direct action of gonadotropins on ovarian tumor cell growth. This review summarizes the key findings and recent advances in our understanding of these peptide hormones in ovarian cancer development and progression and their role in potential future cancer therapy. We will first discuss the supporting evidence and controversies in the "gonadotropin theory" and the use of animal models for exploring the involvement of gonadotropins in the etiology of ovarian cancer. The role of gonadotropins in regulating the proliferation, survival, and metastasis of OEC is next summarized. Relevant data from ovarian surface epithelium, which is widely believed to be the precursor of OEC, are also described. Finally, we will discuss the clinical applications of gonadotropins in ovarian cancer and the recent progress in drug development.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it