Yeast Golden Gate (yGG) for the Efficient Assembly of <i>S. cerevisiae</i> Transcription Units
Bibliographic record
Abstract
We have adapted the Golden Gate DNA assembly method to the assembly of transcription units (TUs) for the yeast Saccharomyces cerevisiae, in a method we call yeast Golden Gate (yGG). yGG allows for the easy assembly of TUs consisting of promoters (PRO), coding sequences (CDS), and terminators (TER). Carefully designed overhangs exposed by digestion with a type IIS restriction enzyme enable virtually seamless assembly of TUs that, in principle, contain all of the information necessary to express a gene of interest in yeast. We also describe a versatile set of yGG acceptor vectors to be used for TU assembly. These vectors can be used for low or high copy expression of assembled TUs or integration into carefully selected innocuous genomic loci. yGG provides synthetic biologists and yeast geneticists with an efficient new means by which to engineer S. cerevisiae.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".