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Record W219529833 · doi:10.1016/j.dib.2015.04.010

Data in support of 5′AMP-activated protein kinase alpha regulates stress granule biogenesis

2015· article· en· W219529833 on OpenAlexafffund
Hicham Mahboubi, Ramla Barisé, Ursula Stochaj

Bibliographic record

VenueData in Brief · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsAMPKStress granuleBiogenesisProtein kinase ACell biologyAMP-activated protein kinaseProtein subunitGranule (geology)ChemistryKinaseGene isoformBiologyBiochemistryGeneMessenger RNA

Abstract

fetched live from OpenAlex

This data article contains insights into the regulation of cytoplasmic stress granules (SGs) by 5'-AMP-activated kinase (AMPK). Our results verify the specific association of AMPK-α2, but not AMPK-α1, with SGs. We also provide validation data for the isoform-specific recruitment of the AMPK-α subunit to SGs using (i) different antibodies and (ii) a distinct cellular model system. In addition, we assess the SG association of the regulatory AMPK β- and γ-subunits. The interpretation of these data and further extensive insights into the regulation of SG biogenesis by AMPK can be found in "5'AMP-activated protein kinase alpha regulates stress granule biogenesis" [1].

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
Research integrity0.0000.000
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 head0.064
GPT teacher head0.309
Teacher spread0.245 · 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.

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

Citations6
Published2015
Admission routes2
Has abstractyes

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