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Record W2011504185 · doi:10.1177/1066896912461527

Benign Epithelial Inclusions in Peripancreatic Lymph Nodes

2012· review· en· W2011504185 on OpenAlexaff
Zuoyu Zheng, Michele Molinari, Heidi Sapp, Shih‐Ming Jung, Ian R. Wanless, Weei‐Yuarn Huang

Bibliographic record

VenueInternational Journal of Surgical Pathology · 2012
Typereview
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsLymphPathologyLymph nodeMedicineMetastasisImmunohistochemistryDifferential diagnosisAdenocarcinomaCancerInternal medicine

Abstract

fetched live from OpenAlex

Benign epithelial inclusions are rarely found in peripancreatic lymph nodes and have not been studied by up-to-date immunohistochemistry. Here, we describe 2 cases of benign epithelial inclusions in the peripancreatic lymph nodes with discussion of differential diagnosis. The first case was a 2.2 cm lymph node from a 61-year-old woman with pancreatic ductal adenocarcinoma. The second case was a 4.3 cm lymph node from a 28-year-old man with distal common bile duct cholangiocarcioma. The epithelial inclusions in the first case consisted of several small squamous cell nests with central duct-like lumina. The lymph node from the second case showed convoluted cystic inclusions lined by a single layer of bland cuboidal epithelium with scattered mucin-producing cells. We also conducted literature review on similar lesions and found that some lesions were associated with pancreatic hetertopia. It is imperative in clinical practice to distinguish these epithelial inclusions in the lymph nodes from tumor metastasis. A hypothetic connection of these benign epithelial inclusions in the peripancreatic lymph nodes to the enigmatic pancreatic lymphoepithelial cysts is suggested.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.086
GPT teacher head0.433
Teacher spread0.347 · 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 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

Citations6
Published2012
Admission routes1
Has abstractyes

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