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Record W2147604929 · doi:10.1002/elps.200410291

Contaminant‐induced current decline in capillary array electrophoresis

2005· article· en· W2147604929 on OpenAlexaff
Robin Coope, Andre Marziali

Bibliographic record

VenueElectrophoresis · 2005
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia
FundersNational Human Genome Research Institute
KeywordsCapillary electrophoresisElectrophoresisAnodeElectrolyteCapillary actionCurrent (fluid)ChromatographyChemistryDegradation (telecommunications)DNAAnalytical Chemistry (journal)Ionic bondingMaterials scienceElectrodeBiochemistryIonComputer sciencePhysicsComposite material

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.223
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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