Contaminant‐induced current decline in capillary array electrophoresis
Bibliographic record
Abstract
High-throughput capillary array electrophoresis (CAE) instruments for DNA sequencing suffer to varying degrees from read length degradation associated with electrophoretic current decline and inhibition or delay in the arrival of fragments at the detector. This effect is known to be associated with residual amounts of large, slow-moving fragments of template or genomic DNA carried through from sample preparation and sequencing reactions. Here, we investigate the creation and expansion of an ionic depletion region induced by overloading the capillary with low-mobility DNA fragments, and the effect of growth of this region on electrophoresis run failure. Slow-moving fragments are analytically and experimentally shown to reduce the ionic concentration of the downstream electrolyte. With injection of large fragments beyond a threshold quantity, the anode-side boundary of the nascent depletion region begins to propagate toward the anode at a rate faster than the contaminant DNA migration. Under such conditions, the depletion region expands, the capillary current declines dramatically, and the electrophoresis run yields a short read length or fails completely.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".