MétaCan
Menu
Back to cohort
Record W2053699276 · doi:10.1021/nl060613v

Carbon Nanotube DNA Sensor and Sensing Mechanism

2006· article· en· W2053699276 on OpenAlexaff
Xiaowu Tang, Sarunya Bansaruntip, Nozomi Nakayama, Erhan Yenilmez, Ying‐Lan Chang, Qian Wang

Bibliographic record

VenueNano Letters · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCarbon nanotubeNanotechnologyOligonucleotideDNAMaterials scienceBiosensorFabricationConductanceDNA–DNA hybridizationNanotubeChemistryPhysics

Abstract

fetched live from OpenAlex

We report the fabrication of single-walled carbon nanotube (SWNT) DNA sensors and the sensing mechanism. The simple and generic protocol for label-free detection of DNA hybridization is demonstrated with random sequence 15mer and 30mer oligonucleotides. DNA hybridization on gold electrodes, instead of on SWNT sidewalls, is mainly responsible for the acute electrical conductance change due to the modulation of energy level alignment between SWNT and gold contact. This work provides concrete experimental evidence on the effect of SWNT-DNA binding on DNA functionality, which will help to pave the way for future designing of SWNT biocomplexes for applications in biotechnology in general and also DNA-assisted nanotube manipulation techniques.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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 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

Citations480
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueNano LettersSame topicCarbon Nanotubes in CompositesFrench-language works237,207