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Record W1981582714 · doi:10.3941/jrcr.v8i3.1459

Inflammatory Pseudotumor of the Liver: A Rare Case of Recurrence Following Surgical Resection

2014· review· en· W1981582714 on OpenAlexaff
Elena P. Scali, Silvia D. Chang, Zuheir Abrahams, Susan Tha, Eric M. Yoshida

Bibliographic record

VenueJournal of Radiology Case Reports · 2014
Typereview
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineMagnetic resonance imagingMalignancyRadiologyInflammatory pseudotumorSurgical resectionUltrasoundResectionRare diseaseLesionComputed tomographySurgical planningSurgeryDiseasePathology

Abstract

fetched live from OpenAlex

Inflammatory pseudotumor (IPT) of the liver is a rare, benign lesion that may be mistaken for malignancy. IPTs are difficult to diagnose due to non-specific clinical, laboratory and imaging features. We report the case of a 38-year old Asian male who presented with fatigue, weight loss and hepatomegaly. He was found to have a large hepatic IPT and underwent surgical resection; approximately two and a half years later, he developed acute cholangitis secondary to IPT recurrence. We present the imaging features of hepatic IPT using ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI). We also review the literature on the diagnosis and management of this disease. The unique features of this case include the IPT's recurrence following surgical resection, large size and multiple modalities presented.

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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.001
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 head0.024
GPT teacher head0.320
Teacher spread0.296 · 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
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

Citations28
Published2014
Admission routes1
Has abstractyes

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