Bibliographic record
Abstract
Ovarian cancer is the prime cause of death from gynecological malignancies in the Western world. In spite of its importance, it is poorly understood and its prognosis remains poor. The most common and lethal of all ovarian cancer subtypes are the high grade serous ovarian carcinomas (HGSOCs). A major problem in their clinical management is the current uncertainty about their cell type of origin, which limits means of early detection and prevention. It has not been resolved whether all HGSOCs originate in oviductal fimbriae or in ovarian surface epithelium (OSE). This review summarises evidence for these two hypotheses and considers the alternative possibility that HGSOCs may arise at both sites. This concept is based on the common embryonic origin of OSE and fimbriae in the coelomic epithelium and evidence of overlapping differentiation between these epithelia in the adult, which suggests incomplete commitment and pleuripotentiality. This hypothesis would account for OSE and fimbriae giving rise to identical carcinomas, and for their susceptibility to neoplastic transformation that is absent in the adjacent extraovarian serosa and oviductal ampulla.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".