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Record W2883334227 · doi:10.1101/370668

Exploring tRNA gene cluster in archaea

2018· preprint· en· W2883334227 on OpenAlexfundno aff

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
FundersCanadian Association for the Study of the Liver
KeywordsArchaeaHorizontal gene transferTransfer RNAGeneBiologyGene clusterGeneticsEuryarchaeotaThree-domain systemGenomeMobile genetic elementsComputational biologyEvolutionary biologyRNA

Abstract

fetched live from OpenAlex

Abstract Shared traits between prokaryotes and eukaryotes are helpful in the understanding of the tree of life evolution. In bacteria and eukaryotes, it has been shown a particular organization of tRNA genes as clusters, but this trait has not been explored in archaea domain. Here, based on analyses of complete and draft archaeal genomes, we demonstrated the prevalence of tRNA gene clusters in archaea. tRNA gene cluster was identified at least in three Archaea class, Halobacteria , Methanobacteria and Methanomicrobia from Euryarchaeota supergroup. Genomic analyses also revealed evidence of tRNA gene cluster associated with mobile genetic elements and horizontal gene transfer inter/intra-domain. The presence of tRNA gene clusters in the three domain of life suggests a role of this type of tRNA gene organization in the biology of the living organisms.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.226
Teacher spread0.189 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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