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Record W2471875020 · doi:10.1007/978-1-59745-232-8_6

Orpheus Recombination

2008· article· en· W2471875020 on OpenAlexaff
Knut Woltjen, Ken‐ichi Ito, Teruhisa Tsuzuki, Derrick E. Rancourt

Bibliographic record

VenueMethods in molecular biology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRecombinationBiologyEvolutionary biologyGeneticsGene

Abstract

fetched live from OpenAlex

In recent years, methods to address the simplification of targeting vector (TV) construction have been developed and validated. Based on in vivo recombination in Escherichia coli, these protocols have reduced dependence on restriction endonucleases, allowing the fabrication of complex TV constructs with relative ease. Using a methodology based on phage-plasmid recombination, we have developed a comprehensive TV construction protocol dubbed Orpheus recombination (ORE). The ORE system addresses all necessary requirements for TV construction; from the isolation of genespecific regions of homology to the deposition of selection/disruption cassettes. ORE makes use of a small recombination plasmid, which bears positive and negative selection markers and a cloned homologous "probe" region. This probe plasmid may be introduced into and excised from phage-borne murine genomic clones by two rounds of single crossover recombination. In this way, desired clones can be specifically isolated from a heterogeneous library of phage. Furthermore, if the probe region contains a designed mutation, it may be deposited seamlessly into the genomic clone. The complete removal of operational sequences allows unlimited repetition of the procedure to customize and finalize TVs within a few weeks. Successful gene-specific clone isolation, point mutations, large deletions, cassette insertions, and finally coincident clone isolation and mutagenesis have all been demonstrated with this method.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods
Teacher disagreement score0.182
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.370
Teacher spread0.348 · 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 teacher head, 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

Citations0
Published2008
Admission routes1
Has abstractyes

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