MétaCan
Menu
Back to cohort
Record W1997389583 · doi:10.1142/s0129156408005849

BIOMOLECULAR SENSING USING CARBON NANOTUBES: A SIMULATION STUDY

2008· article· en· W1997389583 on OpenAlex
G. B. Abadir, Konrad Walus, Robin F. B. Turner, D.L. Pulfrey

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

VenueInternational Journal of High Speed Electronics and Systems · 2008
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsCarbon nanotubeMoleculeMolecular dynamicsMaterials scienceConductanceNanotechnologyLocal density of statesDensity functional theoryElectroluminescenceCarbon fibersChemical physicsFunction (biology)BiosensorComputational chemistryChemistryPhysicsCondensed matter physicsOrganic chemistry

Abstract

fetched live from OpenAlex

A simulation study using molecular dynamics and the density-functional-theory/non-equilibrium-Green's-function approach has been carried out to investigate the potential of carbon nanotubes (CNT) as molecular-scale biosensors. Single molecules of each of two amino acids (isoleucine and asparagine) were used as the target molecules in two separate simulations. The results show a significant suppression of the local density of states (LDOS) in both cases, with a distinct response for each molecule. This is promising for the prospect of CNT-based single-molecule sensors that might depend on the LDOS, e.g., devices that respond to changes in either conductance or electroluminescence.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.022
GPT teacher head0.288
Teacher spread0.266 · 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