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Quantum transport anomalies in DNA containing mispairs

2010· article· en· W2093414777 on OpenAlexaff
Xue‐Feng Wang, Tapash Chakraborty, Julia Berashevich

Bibliographic record

VenueNanotechnology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Manitoba
FundersSoochow UniversityNational Natural Science Foundation of China
KeywordsMaterials scienceAb initioBiasingIonizationDNAElectrodeCharge (physics)Current (fluid)PlatinumLow energyChemical physicsMolecular physicsAtomic physicsVoltageIonPhysical chemistryBiologyPhysicsChemistryThermodynamicsBiochemistry

Abstract

fetched live from OpenAlex

The effect of mispairs on charge transport in DNA of sequence (GC)(TA)(N)(GC)(3) connected to platinum electrodes is studied using the tight-binding model. With parameters derived from an ab initio density functional result, we calculate the current versus bias voltage for DNA with and without a mispair and for different numbers of (TA) basepairs N between the single and triple (GC) basepairs. The current decays exponentially with N under low bias but reaches a minimum under high bias when a multichannel transport mechanism is established. A (GA) mispair substituting a (TA) basepair near the middle of the (TA)(N) sequence usually enhances the current by one order due to its low ionization energy but may decrease the current significantly when an established multichannel mechanism is broken.

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 score0.055
Threshold uncertainty score0.626

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 integrity0.0010.000
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 head0.004
GPT teacher head0.215
Teacher spread0.211 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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