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Record W2154365039 · doi:10.1139/h08-059

Exercise and the fatty liver

2008· review· en· W2154365039 on OpenAlexaffvenue
Natasha A. Spassiani, Jennifer L. Kuk

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2008
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsYork University
Fundersnot available
KeywordsFatty liverMedicineObesityPsychological interventionDiabetes mellitusInternal medicineEndocrinologyPhysical activityIntervention (counseling)DiseaseType 2 diabetesPhysiologyPhysical therapy

Abstract

fetched live from OpenAlex

Fatty liver is an increasingly prevalent condition that is associated with several metabolic derangements, thus necessitating the development of effective therapeutic interventions. Growing evidence from cross-sectional studies suggest that physical activity may be a promising therapy for fatty liver. Unfortunately, longitudinal evidence supporting this observation in humans is sparse, as the majority of intervention studies have examined the relationship between liver fat and physical activity in conjunction with caloric and dietary fat restriction. Studies in rats demonstrate a beneficial effect of exercise on liver fat, mainly in situations of high fat feeding or obesity. Thus, the independent contribution of physical activity on variations in liver fat is unknown, but remains a promising intervention that requires further investigation. There is some evidence to suggest that both physical activity and liver fat are independent correlates of cardiovascular and type 2 diabetes risk. The relative contribution of each remains unclear, but implies that both should be considered when developing therapeutic interventions for chronic metabolic disease.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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)0.0050.003

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 head0.026
GPT teacher head0.281
Teacher spread0.255 · 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

Citations31
Published2008
Admission routes2
Has abstractyes

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