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Record W2808946987 · doi:10.1097/md.0000000000010916

A rare case report of ovarian juvenile granulosa cell tumor with massive ascites as the first sign, and review of literature

2018· article· en· W2808946987 on OpenAlexaff
Liang Ma, Liwen Zhang, Yun Zhuang, Ding Yanbo, Jianping Chen

Bibliographic record

VenueMedicine · 2018
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsEmergent BioSolutions (Canada)
Fundersnot available
KeywordsMedicineAscitesOvarian tumorRadiologyOvarian cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

RATIONALE: Massive ascites as the first sign of ovarian juvenile granulosa cell tumor (JGCT) in an adolescent is an extremely rare, and its clinical features and treatment methods have not been well described. PATIENT CONCERNS: The clinical characteristics, diagnosis, and treatment methods in a 19-year-old girl who presented with massive abdominal distention and ascites was retrospectively reviewed. Abdominopelvic ultrasonography showed a large amount of ascites. The nature of ascites was exudate. All tumor markers were normal, but ascites and serum tumor CA125 levels were significantly increased. Abdominal CT showed left attachment area teratoma and right attachment area capsule solid change. DIAGNOSES: Histological and immunohistochemical results were compatible with JGCT. Based on the FIGO classification, the patient with only malignant ascites was categorized into stage IC. INTERVENTIONS: The patient underwent mass resection with salpingoophorectomy. Following the operation, she received 6 courses of adjuvant chemotherapy with Nedaplatin and Paclitaxel liposome. OUTCOMES: The patient was followed up postoperatively for 6 months to date without recurrence. LESSONS: We should be highly vigilant the JGCT with massive ascites as the first clinical manifestation.

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)0.002
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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