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Record W2782353569 · doi:10.21769/bioprotoc.2674

Targeted Genome Editing of Virulent Phages Using CRISPR-Cas9

2018· article· en· W2782353569 on OpenAlexaff
Marie-Laurence Lemay, Ariane C. Renaud, Geneviève M. Rousseau, Sylvain Moineau

Bibliographic record

VenueBIO-PROTOCOL · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCRISPRBiologyGenome editingLytic cyclePlasmidCas9GenomeHomologous recombinationVirulenceGeneticsBacteriophageLactococcus lactisGeneCre-Lox recombinationGene targetingTemperatenessComputational biologyPhagemidBacteriaVirusEscherichia coli

Abstract

fetched live from OpenAlex

MG1363. The CRISPR-Cas9 system is programmed to cleave a specific region present on the genome of the invading phage, but absent from the recombination template. The system either triggers the recombination event or exerts the selective pressure required to isolate recombinant phages. With this methodology, we generated multiple gene knockouts, a point mutation and an insertion in the genome of the virulent lactococcal phage p2. Considering the broad host range of the plasmids used in this protocol, the latter can be extrapolated to other phage-host pairs.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.327
Teacher spread0.301 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations10
Published2018
Admission routes1
Has abstractyes

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