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Record W1968535877 · doi:10.1002/elps.200500532

Universal interpolating function for the dispersion coefficient of DNA fragments in sieving matrices

2006· article· en· W1968535877 on OpenAlexaff
Jean‐François Mercier, Gary W. Slater

Bibliographic record

VenueElectrophoresis · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReptationDiffusionElectric fieldStatistical physicsField (mathematics)ElectrophoresisFunction (biology)Molecular diffusionScalingDispersion (optics)ChemistryPhysicsThermodynamicsMathematicsOpticsPolymerChromatographyGeometryQuantum mechanics

Abstract

fetched live from OpenAlex

The separation of DNA fragments by (slab or capillary) gel electrophoresis has been studied extensively. To characterize the separation achieved by such systems, one needs to understand the impact (and their dependency upon the experimental quantities) of two physical parameters: the electrophoretic mobility mu and the diffusion coefficient D. Three different regimes have been shown to exist for both mu and D: the Ogston regime, the reptation regime and the reptation with orientation regime (note that separation is only possible for the first two regimes). In the small electric field limit, both mu and D are apparently well described by theories for all three regimes. Unfortunately this results in disjointed scaling laws and no theory-based general equations can apply to all regimes. Recently, an empirical interpolating formula has been proposed that adequately fits the low electric field mobility mu of dsDNA fragments across all three regimes and is compatible with accepted theories. In this article we review and clarify the current state of knowledge regarding the size dependence of the mobility and the diffusion coefficient and propose an interpolating formula for molecular size dependence of the low field diffusion coefficient D. With formulas for both the mobility and the diffusion coefficient as a function of the experimental conditions one could, in principle, optimize any gel/polymer matrix-based electrophoresis system for a wide range of DNA molecular sizes.

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 categoriesnone
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 score0.189
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2006
Admission routes1
Has abstractyes

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