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Record W1991145778 · doi:10.1139/w06-102

An efficient system for markerless gene replacement applicable in a wide variety of enterobacterial species

2007· article· en· W1991145778 on OpenAlexafffundvenue
Aaron P. White, Emma Allen‐Vercoe, Bridget Jones, Rebekah DeVinney, William W. Kay, Michael G. Surette

Bibliographic record

VenueCanadian Journal of Microbiology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Calgary
FundersCanadian Association of Gastroenterology
KeywordsBiologySalmonella entericaGeneEscherichia coliGeneticsMutagenesisSalmonellaVibrio parahaemolyticusEnterobacteriaceaePolymerase chain reactionVibrioGene cassetteVibrio choleraeMicrobiologyComputational biologyMutationBacteriaIntegron

Abstract

fetched live from OpenAlex

We describe an improved allelic-exchange method for generating unmarked mutations and chromosomal DNA alterations in enterobacterial species. Initially developed for use in Salmonella enterica, we have refined the method in terms of time, simplicity, and efficiency. We have extended its use into related bacterial species that are more recalcitrant to genetic manipulations, including enterohemorrhagic and enteropathogenic Escherichia coli and Vibrio parahaemolyticus. Data from over 50 experiments are presented including gene inactivations, site-directed mutagenesis, and promoter exchanges. In each case, desired mutations were identified by polymerase chain reaction screening typically from as few as 10-20 colonies up to a maximum of 300 colonies. The method does not require antibiotic nor nutritional markers in target genes and works efficiently in wild-type strains, obviating the need for specialized hosts or genetic systems. The use is simple, requiring basic laboratory materials, and represents an alternative to existing methods for gene manipulation in the Enterobacteriaceae.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.004

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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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
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

Citations20
Published2007
Admission routes3
Has abstractyes

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