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Record W3121024170 · doi:10.1007/s00239-020-09979-5

Complex Evolution of the Mismatch Repair System in Eukaryotes is Illuminated by Novel Archaeal Genomes

2021· article· en· W3121024170 on OpenAlexfundno aff
Paulo G. Hofstatter, Daniel J. G. Lahr

Bibliographic record

VenueJournal of Molecular Evolution · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersDalhousie UniversityFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsBiologyArchaeaEvolutionary biologyGeneticsGene duplicationGenomeHousekeeping geneDNA repairGeneComputational biology

Abstract

fetched live from OpenAlex

Repairing DNA damage is one of the most important functions of the 'housekeeping' proteins, as DNA molecules are constantly subject to different kinds of damage. An important mechanism of DNA repair is the mismatch repair system (MMR). In eukaryotes, it is more complex than it is in bacteria or Archaea due to an inflated number of paralogues produced as a result of an extensive process of gene duplication and further specialization upon the evolution of the first eukaryotes, including an important part of the meiotic machinery. Recently, the discovery and sequencing of Asgard Archaea allowed us to revisit the MMR system evolution with the addition of new data from a group that is closely related to the eukaryotic ancestor. This new analysis provided evidence for a complex evolutionary history of eukaryotic MMR: an archaeal origin for the nuclear MMR system in eukaryotes, with subsequent acquisitions of other MMR systems from organelles.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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 designObservational
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

Citations15
Published2021
Admission routes1
Has abstractyes

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