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Record W2902649075 · doi:10.1038/s42255-018-0007-6

Interaction between hormone-sensitive lipase and ChREBP in fat cells controls insulin sensitivity

2018· article· en· W2902649075 on OpenAlexaff
Pauline Morigny, Marianne Houssier, Aline Mairal, Claire Ghilain, Étienne Mouisel, Fadila Benhamed, Bernard Masri, Emeline Recazens, Pierre‐Damien Denechaud, Geneviève Tavernier, Sylvie Caspar‐Bauguil, Sam Virtue, Veronika Šrámková, Laurent Monbrun, Anne Mazars, Madjid Zanoun, Sandra Guilmeau, Valentin Barquissau, Diane Beuzelin, Sophie Bonnel, Marie Marquès, Boris Monge-Roffarello, Corinne Lefort, Barbara A. Fielding, Thierry Sulpice, Arne Astrup, Bernard Payrastre, Justine Bertrand‐Michel, Emmanuelle Meugnier, Lætitia Ligat, Frédéric Lopez, Hervé Guillou, Charlotte Ling, Cecilia Holm, Rémi Rabasa‐Lhoret, Wim H. M. Saris, Vladimír Štich, Peter Arner, Mikael Rydén, Cédric Moro, Nathalie Viguerie, Matthew Harms, Stefan Hallén, Antonio Vidal‐Puig, Hubert Vidal, Catherine Postic, Dominique Langin

Bibliographic record

VenueNature Metabolism · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsUniversité de MontréalMontreal Clinical Research Institute
FundersAstraZeneca FranceAstraZenecaAgence Nationale de la RechercheInstitut Universitaire de FranceBritish Heart FoundationConseil Régional Midi-PyrénéesNovo Nordisk FondenFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleMedical Research CouncilEuropean Federation of Pharmaceutical Industries and Associations
KeywordsLipaseInsulin sensitivityInternal medicineEndocrinologyHormone-sensitive lipaseInsulinSensitivity (control systems)HormoneChemistryAdipose tissueMedicineInsulin resistanceLipolysisEnzymeBiochemistry

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations56
Published2018
Admission routes1
Has abstractno

Explore more

Same venueNature MetabolismSame topicLipid metabolism and biosynthesisFrench-language works237,207