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Record W2624092051 · doi:10.1111/evo.13287

Prophage as a genetic reservoir: Promoting diversity and driving innovation in the host community

2017· article· en· W2624092051 on OpenAlexafffund
Asadullah Nadeem, Lindi M. Wahl

Bibliographic record

VenueEvolution · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsProphageBiologyTemperatenessCoevolutionHost (biology)RecombinationGeneticsGenomePopulationGenetic diversityEvolutionary biologyLysogenic cycleBacteriophageGeneEscherichia coli

Abstract

fetched live from OpenAlex

Sequencing of bacterial genomes has revealed an abundance of prophage sequences in many bacterial species. Since these sequences are accessible, through recombination, to infecting phages, bacteria carry an arsenal of genetic material that can be used by these viruses. We develop a mathematical model to isolate the effects of this phenomenon on the coevolution of temperate phage and bacteria. The model predicts that prophage sequences may play a key role in maintaining the phage population in situations that would otherwise favor host cell resistance. In addition, prophage recombination facilitates the existence of multiple phage types, thus promoting diverse co-existence in the phage-host ecosystem. Finally, because the host carries an archive of previous phage strategies, prophage recombination can drive waves of innovation in the host cell population.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.260
Teacher spread0.236 · 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

Citations32
Published2017
Admission routes2
Has abstractyes

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