MétaCan
Menu
Back to cohort
Record W2515307516 · doi:10.1021/acs.macromol.5b00961

Correlated Fluctuations of DNA between Nanofluidic Entropic Traps

2015· article· en· W2515307516 on OpenAlexaff
Alexander Klotz, Mikhail Mamaev, Lyndon Duong, Hendrick W. de Haan, Walter Reisner

Bibliographic record

VenueMacromolecules · 2015
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsOntario Tech UniversityMcGill University
Fundersnot available
KeywordsAntisymmetric relationRelaxation (psychology)Harmonic oscillatorLangevin equationOscillation (cell signaling)HarmonicNormal modeLangevin dynamicsMolecular physicsPhysicsMolecular dynamicsStiffnessMechanicsChemistryOpticsCondensed matter physicsClassical mechanicsStatistical physicsThermodynamicsVibrationQuantum mechanics

Abstract

fetched live from OpenAlex

Here we explore thermally driven contour fluctuations within a single DNA chain partitioned between two embedded cavity reservoirs in a nanofluidic slit. Analysis of integrated cavity intensity suggests that contour is exchanged dynamically between the reservoirs via modes that resemble the symmetric and antisymmetric modes of a coupled harmonic oscillator. The relaxation time of the modes is measured as a function of cavity width and spacing. Langevin dynamics simulations reproduce our observations and motivate a free energy model with a blob-type hydrodynamic friction, developed and used to deduce how the measured relaxation times for the modes depend on device parameters. The relaxation time of the antisymmetric mode was found to be consistent with an excluded volume-based stiffness while the faster symmetric mode depends on additional entropic and elastic parameters.

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 score0.075
Threshold uncertainty score0.550

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 head0.019
GPT teacher head0.217
Teacher spread0.198 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueMacromoleculesSame topicNanopore and Nanochannel Transport StudiesFrench-language works237,207