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Record W4251139549 · doi:10.1385/1-59259-958-3:107

Yeast Transformation by the LiAc/SS Carrier DNA/PEG Method

2005· article· en· W4251139549 on OpenAlexaff
R. Daniel Gietz, Robin A. Woods

Bibliographic record

VenueHumana Press eBooks · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsTransformation (genetics)Transformation efficiencyPlasmidYeastComputer sciencePEG ratioDNAProtocol (science)Computational biologyBiologyGeneticsGeneMedicine

Abstract

fetched live from OpenAlex

The technique for the transformation of Saccharomyces cerevisiae using the LiAc/SS Carrier DNA/PEG method is described. We describe a rapid method, for use when large numbers of transformants are not necessary. A high-efficiency method for the generation of large numbers of transformants is also given. A method for the transformation of plasmid libraries, which includes yeast two-hybrid applications, also is listed to aid the reader in generating transformants to effectively cover the library complexity. Finally, a protocol for transformation using a 96-well format is included for transformation applications that require it.

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: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.010

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 head0.017
GPT teacher head0.315
Teacher spread0.298 · 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

Citations343
Published2005
Admission routes1
Has abstractyes

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