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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 OpenAlexaff
Javier Conde, Morena Scotece, Rodolfo Gómez, Verónica López, Juan J. Gómez‐Reino, Francisca Lago, Oreste Gualillo

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.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.004

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

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

Citations196
Published2011
Admission routes1
Has abstractyes

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