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Record W1596019802 · doi:10.1111/obr.12116

Brown adipose tissue as an anti‐obesity tissue in humans

2013· review· en· W1596019802 on OpenAlexafffundabout
Kanta Chechi, Jan Nedergaard, Denis Richard

Bibliographic record

VenueObesity Reviews · 2013
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersCanadian Institutes of Health ResearchStockholms Universitet
KeywordsBrown adipose tissueAdipose tissueThermogenesisObesityWhite adipose tissueBiologyMedicinePhysiologyBioinformaticsEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

During the 11th Stock Conference held in Montreal, Quebec, Canada, world-leading experts came together to present and discuss recent developments made in the field of brown adipose tissue biology. Owing to the vast capacity of brown adipose tissue for burning food energy in the process of thermogenesis, and due to demonstrations of its presence in adult humans, there is tremendous interest in targeting brown adipose tissue as an anti-obesity tissue in humans. However, the future of such therapeutic approaches relies on our understanding of the origin, development, recruitment, activation and regulation of brown adipose tissue in humans. As reviewed here, the 11th Stock Conference was organized around these themes to discuss the recent progress made in each aspect, to identify gaps in our current understanding and to further provide a common groundwork that could support collaborative efforts aimed at a future therapy for obesity, based on brown adipose tissue thermogenesis.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.029

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 head0.076
GPT teacher head0.383
Teacher spread0.307 · 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; both teacher heads agree on what is shown here.

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

Citations92
Published2013
Admission routes3
Has abstractyes

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