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Record W2152496331 · doi:10.1080/07391102.2014.954315

Binding of nucleobases with graphene and carbon nanotube: a review of computational studies

2014· review· en· W2152496331 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Biomolecular Structure and Dynamics · 2014
Typereview
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNucleobaseGrapheneCarbon nanotubeNanotechnologyMaterials scienceBiosensorChemistryDNA

Abstract

fetched live from OpenAlex

Functionalized carbon nanotubes (CNTs) constitute a new class of nanostructured materials that have vast applications in CNT purification and separation, biosensing, drug delivery, etc. Hybrids formed from the functionalization of CNT with biological molecules have shown interesting properties and have attracted great attention in recent years. Of particular interest is the hybridization of single- or double-stranded nucleic acid (NA) with CNT. Nucleobases, as the building blocks of NA, interact with CNT and contribute strongly to the stability of the NA-CNT hybrids and their properties. In this work, we present a thorough review of previous studies on the binding of nucleobases with graphene and CNT, with a focus on the simulation works that attempted to evaluate the structure and strength of binding. Discrepancies among these works are identified, and factors that might contribute to such discrepancies are discussed.

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.

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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.314
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.012
GPT teacher head0.299
Teacher spread0.287 · 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