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Record W2562987197 · doi:10.14740/gr731w

Non-Alcoholic Fatty Pancreatic Disease: A Review of Literature

2016· review· en· W2562987197 on OpenAlexvenueno aff
Hassan Tariq, Suresh Kumar Nayudu, Sai Akella, Mariela Glandt, Sridhar Chilimuri

Bibliographic record

VenueGastroenterology Research · 2016
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSteatosisFatty liverInsulin resistanceMetabolic syndromePancreatitisGastroenterologyPancreasPancreatic cancerInternal medicineSteatohepatitisDiseaseAcute pancreatitisObesityPathologyCancer

Abstract

fetched live from OpenAlex

There is an epidemic of obesity worldwide. The prevalence of obesity has doubled over the last three decades. Obesity, especially abdominal obesity is associated with insulin resistance that can lead to pancreatic steatosis and non-alcoholic fatty pancreatic disease (NAFPD). NAFPD describes a phenotype entity ranging from deposition of fat in the pancreas to pancreatic inflammation, and resultant fibrosis, which is similar to that of non-alcoholic fatty liver disease (NAFLD). NAFPD may represent a meaningful manifestation of metabolic syndrome. Pancreatic steatosis can be diagnosed on ultrasound, computed tomography (CT) scan or magnetic resonance imaging (MRI). In addition to a correlation between pancreatic steatosis and metabolic syndrome, pancreatic steatosis may lead to a worse outcome in pancreatitis and may be an etiological factor in pancreatic cancer, but we need further research to examine the associations, pathophysiology, and the impact of pancreatic steatosis and NAFPD on the human health.

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)0.001
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.081
GPT teacher head0.441
Teacher spread0.360 · 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 designSystematic review
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

Citations104
Published2016
Admission routes1
Has abstractyes

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