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An Unexplored Diversity of Reverse Transcriptases in Bacteria

2015· review· en· W916359970 on OpenAlexaff
Steven Zimmerly, Li Wu

Bibliographic record

VenueMicrobiology Spectrum · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGroup II intronBiologyGeneticsGenomeBacterial genome sizeIntronBacteriaReverse transcriptaseComputational biologyEvolutionary biologyGenePolymerase chain reactionRNARNA splicing

Abstract

fetched live from OpenAlex

Reverse transcriptases (RTs) are usually thought of as eukaryotic enzymes, but they are also present in bacteria and likely originated in bacteria and migrated to eukaryotes. Only three types of bacterial retroelements have been substantially characterized: group II introns, diversity-generating retroelements, and retrons. Recent work, however, has identified a myriad of uncharacterized RTs and RT-related sequences in bacterial genomes, which exhibit great sequence diversity and a range of domain structures. Apart from group II introns, none of these putative RTs show evidence of active retromobility. Instead, available information suggests that they are involved in useful processes, sometimes related to phages or phage resistance. This article reviews our knowledge of both characterized and uncharacterized RTs in bacteria. The range of their sequences and genomic contexts promises the discovery of new biochemical reactions and biological phenomena.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.047
GPT teacher head0.298
Teacher spread0.251 · 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
GenreReview

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

Citations57
Published2015
Admission routes1
Has abstractyes

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