Detrapping particles in gel electrophoresis: A numerical study of different pulsed field sequences
Bibliographic record
Abstract
Large particles tend to get trapped in dead-ends more often than small particles when electrophoresed in random cross-linked gels. It is known that pulsed electric fields can be used to free particles from these traps, leading to an increase in velocity and improved size separation. Although numerical and theoretical models have been proposed for the mobility of smaller particles in the so-called Ogston sieving limit, the effect of pulsed fields on trapping has not been previously modeled. We present a numerical study of detrapping and we compare our results with those of To and Boyde (To, K.-Y., Boyde, T. R., Electrophoresis 1993, 14, 597). We use an exact numerical method to examine detrapping in various two-dimensional systems of obstacles. We also propose and investigate new ways to optimize the pulse sequence in order to separate particles of different sizes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".