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Record W2986697169 · doi:10.7554/elife.23872.024

Author response: The RNF168 paralog RNF169 defines a new class of ubiquitylated histone reader involved in the response to DNA damage

2017· peer-review· en· W2986697169 on OpenAlexaff
Julianne L. Kitevski-LeBlanc, Amélie Fradet‐Turcotte, Predrag Kukić, Marcus D. Wilson, Guillem Portella, Tairan Yuwen, Stephanie Panier, Shili Duan, Marella D. Canny, Hugo van Ingen, C.H. Arrowsmith, John L. Rubinstein, Michele Vendruscolo, Daniel Durocher, Lewis E. Kay

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsHospital for Sick ChildrenUniversité LavalHôtel-Dieu de QuébecCentre hospitalier universitaire de QuébecLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
Fundersnot available
KeywordsChromatinNucleosomeUbiquitinHistoneDNADNA damageBiologyDNA repairGeneticsCell biologyUbiquitin ligaseComputational biologyChemistryGene

Abstract

fetched live from OpenAlex

A structural model of the dynamic complex comprising the histone reader RNF169 bound to an ubiquitylated nucleosome core particle reveals a three-pronged binding mechanism, which provides specificity for the recognition of DNA double-strand break sites.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.167
Threshold uncertainty score0.558

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1670.066

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 head0.057
GPT teacher head0.358
Teacher spread0.302 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2017
Admission routes1
Has abstractyes

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