Bibliographic record
Abstract
Site-directed mutagenesis has revolutionized the study of protein structure and function by enabling the controlled and systematic production of mutant proteins. Early methods of site-directed mutagenesis involved the use of a mutated oligonucleotide primer to prime synthesis of a target single-stranded DNA template. These approaches were very inefficient, yielding success rates of 1–5% (). A dramatic improvement in the efficiency of generating mutations resulted from the use of single-stranded, uracil-containing DNA molecules isolated from ung − dut− Escherichia coli strains (see Chapter 3). Again, the mutation is introduced in a mutated oligonucleotide primer. Selection against the wild-type sequence parent DNA occurs on transformation into wild-type E. coli. Mutagenesis by this method was relatively efficient, with rates of 15–35%, but required a number of subcloning steps involving single-stranded M13 phage clones (). It was only following the development of the polymerase chain reaction (PCR) that the two concepts were combined, dramatically improving the efficiency of the whole procedure.
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 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.016 |
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".