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Record W4288046809 · doi:10.1042/cs20210506

Targeting skeletal muscle mitochondrial health in obesity

2022· review· en· W4288046809 on OpenAlexafffund
Chantal A. Pileggi, Breana G. Hooks, Ruth McPherson, Robert Dent, Mary‐Ellen Harper

Bibliographic record

VenueClinical Science · 2022
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsSkeletal muscleObesityEndocrinologyInternal medicineWeight lossMetabolismMitochondrionBiologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Metabolic demands of skeletal muscle are substantial and are characterized normally as highly flexible and with a large dynamic range. Skeletal muscle composition (e.g., fiber type and mitochondrial content) and metabolism (e.g., capacity to switch between fatty acid and glucose substrates) are altered in obesity, with some changes proceeding and some following the development of the disease. Nonetheless, there are marked interindividual differences in skeletal muscle composition and metabolism in obesity, some of which have been associated with obesity risk and weight loss capacity. In this review, we discuss related molecular mechanisms and how current and novel treatment strategies may enhance weight loss capacity, particularly in diet-resistant obesity.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.141
GPT teacher head0.473
Teacher spread0.331 · 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

Citations19
Published2022
Admission routes2
Has abstractyes

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