Bibliographic record
Abstract
This article reviews publications dating back more than a century describing investigations of the endometrium, including those examining the relationship between endometrial hyperplasia and carcinoma, the influence of estrogens on the endometrium, and strategies for protecting the endometrium from unopposed estrogen stimulation. Endometrial hyperplasia and carcinoma studies date from before 1900. The influence of endogenous estrogens on the endometrium became evident with observations of endometrial hyperplasia and/or carcinoma in women with estrogen-secreting tumors or polycystic ovarian disease. Later, observational studies and randomized, controlled trials suggested a relationship between unopposed estrogens and endometrial cancer and hyperplasia. The first, and to date only, effective clinical strategy for protecting the endometrium from unopposed estrogen stimulation has been the use of progestins. A new approach for endometrial protection in menopausal therapy is the pairing of a selective estrogen receptor modulator (SERM) with estrogen(s), also known as a tissue selective estrogen complex (TSEC). Effective protection of the endometrium as well as treatment of menopausal symptoms and prevention of osteoporosis would be key elements for a clinically useful TSEC.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".