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Record W2888711287 · doi:10.1002/gcc.22649

Novel <i>EPC1</i> gene fusions in endometrial stromal sarcoma

2018· article· en· W2888711287 on OpenAlexaff
Brendan C. Dickson, Amy Lum, David Swanson, Marcus Q. Bernardini, Terrence J. Colgan, Patricia A. Shaw, Stephen Yip, Cheng‐Han Lee

Bibliographic record

VenueGenes Chromosomes and Cancer · 2018
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsSpinal Cord Injury BCBC Cancer AgencyPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health NetworkUniversity of British ColumbiaVancouver General HospitalMount Sinai Hospital
Fundersnot available
KeywordsEndometrial stromal sarcomaStromal cellSarcomaCancer researchFusion geneMesenchymal stem cellBiologyMedicineGeneOncologyInternal medicinePathologyGenetics

Abstract

fetched live from OpenAlex

Endometrial stromal sarcoma encompasses a heterogeneous group of uterine mesenchymal neoplasms, which are currently divided into low-grade and high-grade subtypes. Low-grade endometrial stromal sarcoma is morphologically bland; molecularly, these tumors frequently contain JAZF1-SUZ12, JAZF1-PHF1, and EPC1-PHF1 fusions. In contrast, high-grade endometrial stromal sarcoma is characterized by morphologically undifferentiated neoplasms with high-grade nuclear features; these tumors likewise appear to be genetically diverse with YWHAE-NUTM2 and ZC3H7B-BCOR representing the most frequent gene fusions. Herein, we describe two novel EPC1 fusion genes in endometrial stromal sarcoma: EPC1-SUZ12 and EPC1-BCOR. Both tumors were characterized be an aggressive clinical course.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.297
Teacher spread0.271 · 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 designObservational
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

Citations65
Published2018
Admission routes1
Has abstractyes

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