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Record W2138202356 · doi:10.1210/edrv.22.2.0422

Ovarian Surface Epithelium: Biology, Endocrinology, and Pathology*

2001· review· en· W2138202356 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEndocrine Reviews · 2001
Typereview
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsBritish Columbia Centre of Excellence for Women's HealthUniversity of British Columbia
FundersNational Cancer InstituteCanadian Institutes of Health Research
KeywordsEpitheliumPathologyBiologyEndocrinologyInternal medicineMedicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.090
GPT teacher head0.395
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it