Endometriosis and endometriosis-associated cancers: new insights into the molecular mechanisms of ovarian cancer development
Bibliographic record
Abstract
Endometriosis is a fascinating disease that we strive to better understand. Molecular techniques are shedding new light on many important aspects of this disease: from pathogenesis to the recognition of distinct disease variants like deep infiltrating endometriosis. The observation that endometriosis is a cancer precursor has now been strengthened with the knowledge that mutations that are present in endometriosis-associated cancers can be found in adjacent endometriosis lesions. Recent genomic studies, placed in context, suggest that deep infiltrating endometriosis may represent a benign neoplasm that invades locally but rarely metastasises. Further research will help elucidate distinct aberrations which result in this phenotype. With respect to identifying those patients who may be at risk of developing endometriosis-associated cancers, a combination of molecular, pathological, and inheritance markers may define a high-risk group that might benefit from risk-reducing strategies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".