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Record W2090716605 · doi:10.5402/2012/878635

The Multifaceted Granulosa Cell Tumours—Myths and Realities: A Review

2012· review· en· W2090716605 on OpenAlexaff
Rani Kanthan, Jenna‐Lynn Senger, Selliah Kanthan

Bibliographic record

VenueISRN Obstetrics and Gynecology · 2012
Typereview
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsPathologicalMedicineContext (archaeology)AbdomenRetrospective cohort studyPathologyGeneral surgeryRadiologyBiology

Abstract

fetched live from OpenAlex

Background. Granulosa cell tumors (GCTs), representing ~2% of ovarian tumours, are poorly understood neoplasms with unpredictable and undetermined biological behaviour. Design. 5 unusual presentations of GCT and a retrospective 14-year (1997-2011) surgical pathology review based on patient sex, age, tumour type and concurrent pathology findings are presented to discuss the "myths and realities" of GCTs in the context of relevant evidence-based literature. Results. The 5 index cases included (1) a 5 month-old boy with a left testicular mass, (2) a 7-day-old neonate with a large complex cystic mass in the abdomen, (3) a 76-year-old woman with an umbilical mass, (4) a 64-year-old woman with a complex solid-cystic pelvic mass, and (5) a 45 year-old woman with an acute abdomen. Pathological analysis confirmed the final diagnosis as (1) juvenile GCT, (2) macrofollicular GCT, (3) recurrent GCT 32 years later, (4) collision tumour: colonic adenocarcinoma and GCT, and (5) ruptured GCT. Conclusion. GCT is best considered as an unusual indolent neoplasm of low malignant potential with late recurrences that can arise in the ovaries and testicles in both the young and the old. Multifaceted clinical presentations coupled with the unpredictable biological behaviour with late relapses are diagnostic pitfalls necessitating a high degree of suspicion for accurate clinical and pathological diagnosis.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.327
Teacher spread0.281 · 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 designNot applicable
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

Citations31
Published2012
Admission routes1
Has abstractyes

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