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Record W4392508896 · doi:10.1038/s43018-024-00742-z

Cytidine deaminases APOBEC3C and APOBEC3D promote DNA replication stress resistance in pancreatic cancer cells

2024· article· en· W4392508896 on OpenAlexafffund
Tajinder Ubhi, Olga Zaslaver, Andrew T. Quaile, Dennis Plenker, Pinjiang Cao, Nhu‐An Pham, Gun-Ho Jang, Grainne M. O’Kane, Faiyaz Notta, Jason Moffat, Julie M. Wilson, Steven Gallinger, Beáta G. Vértessy, David A. Tuveson, Hannes Röst, Grant W. Brown

Bibliographic record

VenueNature Cancer · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health NetworkOntario Institute for Cancer Research
FundersCanadian Friends of Hebrew UniversityCanadian Institutes of Health ResearchHospital for Sick ChildrenTerry Fox Research InstituteMagyar Tudományos AkadémiaNational Cancer InstituteUniversity of TorontoNemzeti Kutatási, Fejlesztési és Innovaciós AlapHungarian Scientific Research FundMagyar Tudományos Akadémia Számítástechnikai és Automatizálási KutatóintézetHebrew University of JerusalemCanadian Cancer Society Research InstituteNational Institutes of HealthU.S. Department of Health and Human ServicesCanada Research ChairsGovernment of OntarioLustgarten FoundationGovernment of CanadaGlaxoSmithKlinePrincess Margaret Cancer FoundationCanada Foundation for InnovationSimons FoundationOntario Institute for Cancer Research
KeywordsCytidinePancreatic cancerCytidine deaminaseCancerCancer researchBiologyGeneticsDNACell biologyEnzymeBiochemistry

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 score0.002
Threshold uncertainty score0.007

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.272
Teacher spread0.267 · 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

Citations24
Published2024
Admission routes2
Has abstractno

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