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Record W2351557437 · doi:10.1097/pgp.0000000000000292

Mitotically Active Sclerosing Stromal Tumor of the Ovary: Report of a Case Series With Parallels to Mitotically Active Cellular Fibroma

2016· article· en· W2351557437 on OpenAlexaff
Emily A. Goebel, W. Glenn McCluggage, Joanna C. Walsh

Bibliographic record

VenueInternational Journal of Gynecological Pathology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsStromal cellOvaryFibromaPathologyBiologyMitosisNeoplasmCancer researchMedicineEndocrinologyCell biology

Abstract

fetched live from OpenAlex

Sclerosing stromal tumor of the ovary is a rare neoplasm that typically occurs in the second and third decades of life. To date, all reported cases have behaved in a benign manner. In their usual form, these neoplasms exhibit scant, if any, mitotic activity. Herein, we report a case series of 6 sclerosing stromal tumors with increased mitotic activity (between 7 and 12 mitoses per 10 high-power fields in the most mitotically active areas). Follow-up is available in 4 of 6 cases (ranging from 3 wk to 68 mo) and 1 tumor recurred within the pelvis. We suggest that the term mitotically active sclerosing stromal tumor is used for such neoplasms and draw parallels with mitotically active cellular fibroma, another benign ovarian stromal neoplasm which occasionally recurs locally, but which does not metastasize.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2016
Admission routes1
Has abstractyes

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