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Record W2523786059 · doi:10.1155/2016/2059245

The Effect of Bariatric Surgery on the Spectrum of Fatty Liver Disease

2016· review· en· W2523786059 on OpenAlexaff
Jordan J. Nostedt, Noah J. Switzer, Richdeep S. Gill, Jerry T. Dang, Daniel W. Birch, Christopher de Gara, Robert J. Bailey, Shahzeer Karmali

Bibliographic record

VenueCanadian Journal of Gastroenterology and Hepatology · 2016
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsRoyal Alexandra HospitalUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsNonalcoholic fatty liver diseaseMedicineCirrhosisFatty liverMetabolic syndromeObesityDiseaseFibrosisGastroenterologyInternal medicineLiver diseaseSurgery

Abstract

fetched live from OpenAlex

Nonalcoholic fatty liver disease is becoming one of the most common causes of liver disease in the western world. The most significant risk factors are obesity and the metabolic syndrome for which bariatric surgery has been shown to be an effective treatment. However, the effects of bariatric surgery on nonalcoholic fatty liver disease, specifically liver fibrosis and cirrhosis, are not well established. We review published bariatric surgery outcomes with respect to nonalcoholic liver disease. On the basis of this review we suggest that bariatric surgery may provide a viable treatment option for the treatment of nonalcoholic fatty liver disease, including patients with fibrosis and compensated cirrhosis, and that this topic should be a target of future investigation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.256
Teacher spread0.237 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Gastroenterology and HepatologySame topicLiver Disease Diagnosis and TreatmentFrench-language works237,207