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Record W2912422712 · doi:10.1074/jbc.ra118.005135

The orphan nuclear receptor Nor1/Nr4a3 is a negative regulator of β-cell mass

2019· article· en· W2912422712 on OpenAlexafffund
Anne-Françoise Close, Nidheesh Dadheech, Bárbara Scoralick Villela, Claude Rouillard, Jean Buteau

Bibliographic record

VenueJournal of Biological Chemistry · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsUniversité LavalDiabetes CanadaCentre hospitalier universitaire de QuébecUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of AlbertaWallonie-Bruxelles InternationalAlberta Diabetes FoundationAlberta InnovatesGovernment of Canada
KeywordsNerve growth factor IBNuclear receptorBiologyGene knockdownGlucose homeostasisNeuron-derived orphan receptor 1Knockout mouseApoptosisOrphan receptorEndocrinologyIsletCellCell biologyInternal medicineReceptorCancer researchTranscription factorGeneticsGeneDiabetes mellitusMedicine

Abstract

fetched live from OpenAlex

expression was up-regulated in islets of individuals with type 2 diabetes. Altogether, our results uncover that Nor1 negatively regulates β-cell mass. Nor1 represents a promising molecular target in diabetes treatment to prevent β-cell destruction.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.022
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.230
Teacher spread0.210 · 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 teacher head, not a consensus.

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

Citations33
Published2019
Admission routes2
Has abstractyes

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