MétaCan
Menu
Back to cohort
Record W2898997658 · doi:10.14740/jem.v8i5.528

Irisin: As a Therapeutic Target for Metabolic Disorders

2018· article· en· W2898997658 on OpenAlexvenueno aff
Ikram Ullah Khan

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2018
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsMyokineFNDC5MedicineAdipose tissueEndocrinologyDiabetes mellitusInternal medicineSkeletal muscleBioinformaticsFibronectinBiologyBiochemistry

Abstract

fetched live from OpenAlex

During physical activity, muscle expresses a panel of proteins named as myokines which exert beneficial effects on the distant organs of the body. Irisin is a relatively newly discovered myokine mainly secreted by the skeletal muscles. This myokine is a cleavage fragment of a transmembrane protein known as fibronectin domain-containing protein 5 (FNDC5). Irisin is known to have multi-spectrum functions including browning of adipose tissue (BAT), enhancing insulin sensitivity, cognition, osteogenesis and metabolism. Due to these functions, irisin has a wide range of therapeutic effects on obesity, diabetes mellitus, hypertension, cardiovascular diseases, chronic kidney diseases, cancer and dementia. In current, our focus is emphasized upon the therapeutic aspects of irisin and its possible role in the diagnoses of various metabolic disorders. J Endocrinol Metab. 2018;8(5):87-93 doi: https://doi.org/10.14740/jem528w

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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.317
Teacher spread0.296 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Endocrinology and MetabolismSame topicAdipose Tissue and MetabolismFrench-language works237,207