MétaCan
Menu
Back to cohort
Record W2114906642 · doi:10.2174/138161207781039652

Non-Alcoholic Fatty Liver Disease in the Metabolic Syndrome

2007· review· en· W2114906642 on OpenAlexaff
Giuseppe Palasciano, Antonio Moschetta, Vincenzo Ostilio Palmieri, Ignazio Grattagliano, Gianluca Iacobellis, Piero Portincasa

Bibliographic record

VenueCurrent Pharmaceutical Design · 2007
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsMcMaster University
FundersMinistero dell'Università e della Ricerca
KeywordsFatty liverMetabolic syndromeSteatohepatitisMedicineSteatosisCirrhosisHyperlipidemiaInternal medicineDiabetes mellitusDiseaseOxidative stressGastroenterologyObesityEndocrinology

Abstract

fetched live from OpenAlex

Non-alcoholic fatty liver disease (NAFLD) is often associated with features of the metabolic syndrome, carrying an increased risk to develop non-alcoholic steatohepatitis (NASH), the inflammatory form of liver steatosis. Epidemiological data confirm that obesity, diabetes, hypertension and hyperlipidemia are frequently found in NAFLD and worsen its prognosis because of increased risk of fibrotic evolution, eventually leading to liver cirrhosis. Recent studies confirm the close relationship between the metabolic syndrome and liver steatosis, and further support the detrimental role of oxidative stress and lipid peroxidation, which are pathophysiological processes present in both conditions. Novel diagnostic tools and life style modifications together with targeted therapeutic actions are urgently needed for the management of liver dysfunction in course of metabolic syndrome.

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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.324
GPT teacher head0.476
Teacher spread0.153 · 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

Citations48
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Pharmaceutical DesignSame topicLiver Disease Diagnosis and TreatmentFrench-language works237,207