Electrophoresis and Blotting of <scp>DNA</scp>
Bibliographic record
Abstract
Abstract Deoxyribonucleic acid (DNA) electrophoresis and blotting are techniques commonly used to visualise DNA. Both techniques use simple, inexpensive protocols that rely on fundamental properties of DNA, and these protocols have changed little since they were introduced. Electrophoresis relies on the negative electrical charge of DNA to draw these molecules through a gel, separating DNA molecules on the basis of size. Southern blotting makes use of sequence complementarity to identify specific DNA fragments on the basis of their sequences. Despite the introduction of more powerful methods such as polymerase chain reaction and DNA sequencing, electrophoresis and blotting techniques are still widely used to identify DNA fragments of interest, including the identification of unusual structures within DNA and the analysis of larger fragments which are not easily analysed by other methods. Key Concepts: DNA electrophoresis and blotting are fundamental methods of molecular biology. Basic physical and chemical properties of DNA are used to analyse unknown sequences. Gel electrophoresis uses an electrical current to separate DNA by size. Southern blotting locates a specific DNA sequence on a gel using a probe sequence that is its chemical match. Minor variations on these procedures can improve results for specific experiments. These techniques are still used to analyse unknown DNA molecules and identify DNA fragments of interest. The principles behind electrophoresis and blotting can also be seen in newer methods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.018 |
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".