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Record W3007427066 · doi:10.1126/scitranslmed.aaw1868

Long noncoding RNA <i>SNHG12</i> integrates a DNA-PK–mediated DNA damage response and vascular senescence

2020· article· en· W3007427066 on OpenAlexaff
Stefan Haemmig, Dafeng Yang, Xinghui Sun, Debapria Das, Siavash Ghaffari, Roberto Molinaro, Lei Chen, Yihuan Deng, Dan Freeman, Norman Moullan, Yevgenia Tesmenitsky, Akm Khyrul Wara, Viorel Simion, Eugenia Shvartz, James F. Lee, Tianlun Yang, Galina Sukova, Jarrod A. Marto, Peter H. Stone, Warren L. Lee, Johan Auwerx, Peter Libby, Mark W. Feinberg

Bibliographic record

VenueScience Translational Medicine · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsSt. Michael's Hospital
FundersNational Institutes of HealthAmerican Heart Association
KeywordsDNA damageBiologySenescenceGene knockdownTelomereCancer researchCell biologyDNA repairDNAGeneGenetics

Abstract

fetched live from OpenAlex

expression was also reduced in pig and human atherosclerotic specimens and correlated inversely with DNA damage and senescent markers. These findings reveal a role for this lncRNA in regulating DNA damage repair in the vessel wall and may have implications for chronic vascular disease states and aging.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.289
Teacher spread0.271 · 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

Citations136
Published2020
Admission routes1
Has abstractyes

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