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Record W2167574371 · doi:10.1677/jme.0.0310001

Agonist-bound nuclear receptors: not just targets of coactivators

2003· review· en· W2167574371 on OpenAlexafffund
Isabelle Fernandes, John H. White

Bibliographic record

VenueJournal of Molecular Endocrinology · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsNuclear receptorTransactivationPELP-1Transcription factorAgonistReceptorCell biologyNuclear receptor coactivator 1Psychological repressionEstrogen-related receptor gammaTranscription coregulatorBiologyChemistryBiochemistryGene expressionGeneTranscriptional regulation

Abstract

fetched live from OpenAlex

Members of the nuclear receptor superfamily of ligand-regulated transcription factors are targets of a wide range of lipophilic signaling molecules as well as several drugs and xenobiotics that modulate many aspects of physiology and metabolism. Agonist binding to receptors is associated with recruitment of coactivators, which are essential for activation of target gene transcription. However, several biochemical and molecular genetic studies have shown that a full understanding of the function of agonist-bound receptors must also accommodate the recruitment of corepressors. These factors may attenuate agonist-induced transactivation, act more transiently as part of a cycle of cofactors recruited to target promoters by ligand-bound receptors, or function in hormone-dependent repression of target gene expression.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.298
Teacher spread0.278 · 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 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

Citations16
Published2003
Admission routes2
Has abstractyes

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