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Record W2908217616 · doi:10.15698/mic2019.01.665

Guidelines for DNA recombination and repair studies: Mechanistic assays of DNA repair processes

2019· review· en· W2908217616 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrobial Cell · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsDiscovery Centre
FundersNational Institute of Environmental Health SciencesNational Institute of General Medical SciencesBiotechnology and Biological Sciences Research CouncilNational Cancer InstituteNational Institutes of HealthAgence Nationale de la RechercheWellcome TrustU.S. Department of Defense
KeywordsDNA repairMutagenesisDNAHomologous recombinationComputational biologyRecombinationBiologyGeneticsChemistryMutationGene

Abstract

fetched live from OpenAlex

Guidelines for DNA recombination and repair studies: Mechanistic assays of DNA repair processes – Klein et al. Genomes are constantly in flux, undergoing changes due to recombination, repair and mutagenesis. In vivo, many of such changes are studies using reporters for specific types of changes, or through cytological studies that detect changes at the single-cell level. Single molecule assays, which are reviewed here, can detect transient intermediates and dynamics of events. Biochemical assays allow detailed investigation of the DNA and protein activities of each step in a repair, recombination or mutagenesis event. Each type of assay is a powerful tool but each comes with its particular advantages and limitations. Here the most commonly used assays are reviewed, discussed, and presented as the guidelines for future studies.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.090
GPT teacher head0.359
Teacher spread0.269 · 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