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Record W2130821807 · doi:10.1148/rg.294085748

A Clinical and Radiologic Review of Uncommon Types and Causes of Pancreatitis

2009· review· en· W2130821807 on OpenAlexaff
Krishna Shanbhogue, Najla Fasih, Venkateswar R. Surabhi, Geoffrey P. Doherty, Divya Krishna Prasad Shanbhogue, Sumer Kumar Sethi

Bibliographic record

VenueRadiographics · 2009
Typereview
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicinePancreatitisRadiologyGeneral surgeryMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

Acute pancreatitis is one of the most common conditions for which emergent imaging is indicated. Alcohol consumption and cholelithiasis are the most common causes of acute pancreatitis in adults, whereas the majority of cases in children are idiopathic or secondary to trauma. A wide variety of structural and biochemical abnormalities may also cause pancreatitis. Although in some cases it is difficult to identify the specific cause of the disease radiologically, certain uncommon types of acute or chronic pancreatitis may have unique imaging features that can help the radiologist make an accurate diagnosis. These unusual types include autoimmune pancreatitis, groove pancreatitis, tropical pancreatitis, hereditary pancreatitis, and pancreatitis in ectopic or heterotopic pancreatic tissue. Pancreatitis may occasionally be seen in association with cystic fibrosis or pancreas divisum, or secondary to worm infestation of the pancreaticobiliary tree (eg, by Ascaris lumbricoides). In addition, primary pancreatic and duodenal masses may occasionally manifest as acute or recurrent acute pancreatitis. Knowledge of the classic imaging findings of these entities allows prompt recognition of the relevant pathologic condition, thereby preventing misdiagnosis and subsequent inappropriate or delayed management.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.008
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.064
GPT teacher head0.391
Teacher spread0.328 · 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

Citations178
Published2009
Admission routes1
Has abstractyes

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