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Mucinous Ovarian Tumors of Mullerian-type: An Analysis of 17 Cases Including Borderline Tumors and Intraepithelial, Microinvasive, and Invasive Carcinomas

2005· review· en· W2068368161 on OpenAlexaff
Val rie Dub, Michel Roy, Marie Plante, Marie‐Claude Renaud, Bernard T tu

Bibliographic record

VenueInternational Journal of Gynecological Pathology · 2005
Typereview
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsHôtel-Dieu de Québec
Fundersnot available
KeywordsSerous fluidMedicinePathologyStage (stratigraphy)Mucinous carcinomaOvaryAdenocarcinomaInternal medicineCancerBiology

Abstract

fetched live from OpenAlex

Mullerian-type mucinous tumors (MMTs) of the ovary are characterized by a papillary architecture similar to that of serous tumors and a content of endocervical-like mucinous epithelium. The latter may be admixed with other mullerian-type epithelia, including those of serous, endometrioid, and squamous types, and indifferent eosinophilic epithelial cells. We analyzed 17 MMTs, including 12 borderline tumors, 2 intraepithelial carcinomas, 2 microinvasive carcinomas, and 1 invasive carcinoma. Fourteen of 16 tumors (88%) with available staging were stage I; the remaining two cases (both borderline) were stage IIa and IIIc. Endometriosis was identified in eight cases (47%). Only two patients (12%) had bilateral tumors, a frequency of bilaterality lower than in previous studies. Five patients (31%) had conservative treatment consisting of a cystectomy or unilateral salpingo-oophorectomy. All patients had a favorable outcome, with no recurrences or disease-related deaths, regardless of the presence of high mitotic index, intraepithelial carcinoma, microinvasion, bilaterality, conservative treatment, or advanced stage. This indolent behavior of MMTs is similar to that previously reported, but additional cases of invasive carcinomas in this category are needed to better define their outcome.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.866
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.379
Teacher spread0.303 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations51
Published2005
Admission routes1
Has abstractyes

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