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Record W2151041597 · doi:10.1186/1758-5996-3-29

The macrophage at the intersection of immunity and metabolism in obesity

2011· article· en· W2151041597 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDiabetology & Metabolic Syndrome · 2011
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsMcMaster Children's HospitalMcMaster University
FundersHamilton Health Sciences
KeywordsMedicineInflammationInsulin resistanceObesityImmune systemAdipose tissueType 2 diabetesMacrophageDiabetes mellitusImmunityBioinformaticsImmunologyInternal medicineEndocrinologyBiology

Abstract

fetched live from OpenAlex

Obesity is a worldwide pandemic representing one of the major challenges that societies face around the globe. Identifying the mechanisms involved in its development and propagation will help the development of preventative and therapeutic strategies that may help control its rising rates.Obesity is associated with chronic low-grade inflammation, and this is believed to be one of the major contributors to the development of insulin resistance, which is an early event in obesity and leads to type 2 diabetes when the pancreas fails to keep up with increased demand for insulin. In this review, we discuss the role of macrophages in mediation of inflammation in obesity in metabolic organs including adipose tissue, skeletal muscle and liver. The presence of immune cells at the interface with metabolic organs modulates both metabolic function and inflammatory responses in these organs, and may provide a potential therapeutic target to modulate metabolic function in 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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