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Record W2571353014 · doi:10.1016/j.ccell.2016.12.002

Epigenetic siRNA and Chemical Screens Identify SETD8 Inhibition as a Therapeutic Strategy for p53 Activation in High-Risk Neuroblastoma

2017· article· en· W2571353014 on OpenAlexafffund
Veronica Veschi, Zhihui Liu, Ty C. Voss, Laurent Ozbun, Berkley E. Gryder, Chunhua Yan, Ying Hu, Anqi Ma, Jian Jin, Sharlyn J. Mazur, Norris Lam, Bárbara Kunzler Souza, Giuseppe Giannini, Gordon L. Hager, C.H. Arrowsmith, Javed Khan, Ettore Appella, Carol J. Thiele

Bibliographic record

VenueCancer Cell · 2017
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsStructural Genomics ConsortiumUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institutes of HealthFundação de Amparo à Pesquisa do Estado de São PauloOntario Genomics InstituteCanada Foundation for InnovationOntario Ministry of Economic Development and InnovationWellcome TrustEshelman Institute for Innovation, University of North Carolina at Chapel HillSt. Baldrick's FoundationMinistero dell’Istruzione, dell’Università e della RicercaAbbVieJanssen BiotechInnovative Medicines InitiativeAssociazione Italiana per la Ricerca sul CancroWellcomeMerckTakeda Pharmaceuticals U.S.A.PfizerBoehringer Ingelheim
KeywordsEpigeneticsDruggabilityChromatinBiologySmall interfering RNACancer researchMethyltransferaseGeneticsBioinformaticsCell biologyRNAGeneMethylation

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 score0.004
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
GPT teacher head0.353
Teacher spread0.316 · 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

Citations128
Published2017
Admission routes2
Has abstractno

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