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Record W2040156743 · doi:10.1116/1.1688360

Numerical simulations of variable range hopping conductivity in deoxyguanosine deoxyribose nucleic acid nucleoside films

2004· article· en· W2040156743 on OpenAlexafffund
Mahi R. Singh, Chi-Ming Tsang

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeoxyriboseVariable-range hoppingThermal conductionConductivityNucleic acidMaterials scienceDeoxyguanosineBond lengthAmorphous solidCondensed matter physicsCrystallographyChemistryComposite materialDNACrystal structurePhysical chemistryPhysicsBiochemistry

Abstract

fetched live from OpenAlex

Numerical simulations are performed for conductivity due to the variable range hopping conduction in deoxyribose nucleic acid nucleotides (deoxyguanosine). Self-assembled deoxyguanosine (SAD) crystals are composed of H-bonded planar ribbons, which tend to stack and form solid-state fibers. These ribbons are connected to each other by a π–π bond and form crystalline and amorphous films. We consider that the carriers are localized in H bond and π–π bond sites and the hopping conduction is the result of many series of hops in these sites. The electric field and temperature dependent conductivity expressions are used to explain the conductivity experiments of SAD films. Good agreement between theory and experiment is found.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2004
Admission routes2
Has abstractyes

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