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Record W2026830291 · doi:10.1088/0957-4484/20/2/025612

Microcapsule carbon nanotube devices for therapeutic applications

2008· article· en· W2026830291 on OpenAlexaff
Arun Kulamarva, Pavan M. V. Raja, Jasmine Bhathena, Hongmei Chen, Saikat Talapatra, Pulickel M. Ajayan, Omkaram Nalamasu, Satya Prakash

Bibliographic record

VenueNanotechnology · 2008
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsMcGill University
Fundersnot available
KeywordsCarbon nanotubeNanotechnologyMaterials scienceBiomedicineNanomaterialsBioinformatics

Abstract

fetched live from OpenAlex

Carbon nanotubes are a new class of nanomaterials that have immense potential in the field of biomedicine. Their ability to carry large quantities of therapeutic molecules makes them prime candidates for providing targeted delivery of therapeutics for use in various diseases. However, their utility is limited due to the problems faced during their delivery to target sites. This article for the first time describes the design of a novel microcapsule carbon nanotube targeted delivery device. This device has potential in the targeted delivery of carbon nanotubes in suitable membranes along with their cargo, safely and effectively to the target loci.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.357

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 integrity0.0000.000
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 head0.265
Teacher spread0.243 · 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

Citations20
Published2008
Admission routes1
Has abstractyes

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