MétaCan
Menu
Back to cohort
Record W2143085509 · doi:10.1002/biof.185

Adipokines: Biofactors from white adipose tissue. A complex hub among inflammation, metabolism, and immunity

2011· review· en· W2143085509 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.

Bibliographic record

VenueBioFactors · 2011
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsTellabs (Canada)
FundersInstituto de Salud Carlos IIINational Institutes of HealthXunta de Galicia
KeywordsAdipokineAdiponectinAdipose tissueLeptinResistinInflammationParacrine signallingInternal medicineWhite adipose tissueMedicineEndocrine systemEndocrinologyBiologyObesityHormoneInsulin resistanceReceptor

Abstract

fetched live from OpenAlex

Until the identification of leptin, the first adipokine discovered in 1994, adipose tissue was considered only as an energy storage tissue. However, it is now clear that adipose tissue is an endocrine/paracrine/autocrine organ, which plays a relevant role in physiopathology of several inflammatory diseases. Actually, it is mainly involved not only in the low-grade inflammatory status in obesity but also in other relevant inflammatory conditions and autoimmune disorders. In this review article, we discuss the main biological activities of leptin, adiponectin, lipocalin-2, resistin, and visfatin, as well as their contributions to certain inflammatory conditions.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.306
Teacher spread0.250 · 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