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Record W2279478471 · doi:10.1021/acs.macromol.5b02240

Nonequilibrium Dynamics of Nanochannel Confined DNA

2016· article· en· W2279478471 on OpenAlexafffund
Ahmed Khorshid, Susan Amin, Zhiyue Zhang, Takahiro Sakaue, Walter Reisner

Bibliographic record

VenueMacromolecules · 2016
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesJapan Society for the Promotion of ScienceCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and Technology
KeywordsNon-equilibrium thermodynamicsMolecular dynamicsDynamics (music)DNAChemical physicsStatistical physicsChemistryNanotechnologyMaterials sciencePhysicsComputational chemistryThermodynamics

Abstract

fetched live from OpenAlex

We show that the dynamic nonequilibrium segmental concentration profile of a single nanochannel confined DNA molecule can be described via a partial differential evolution equation based on nonlinear diffusion, using an approach analogous to that used in the description of many-molecule systems such as polymer solutions. This equation can describe the segmental concentration profile of a single polymer along the nanochannel as a function of time for chain behavior ranging from states of high compression to equilibrium. In particular, to demonstrate the generality of our approach, we show that our model can describe two distinct types of experimental behavior generated via a sliding bead assay, symmetric relaxation resulting from free expansion of the polymer after compression, and the evolution of DNA concentration “shock waves” as a molecule is driven from equilibrium to a compressed state.

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 score0.037
Threshold uncertainty score0.527

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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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

Citations23
Published2016
Admission routes2
Has abstractyes

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