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Record W2079385972 · doi:10.1016/j.btre.2014.06.003

Reusable urine glucose sensor based on functionalized graphene oxide conjugated Au electrode with protective layers

2014· article· en· W2079385972 on OpenAlexaff
Hye Youn Kim, Kuk Jin Jang, Murugan Veerapandian, Hyung Chul Kim, Yeong Tai Seo, Kook-Nyung Lee, Min‐Ho Lee

Bibliographic record

VenueBiotechnology Reports · 2014
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsUniversité de Montréal
FundersMinistry of Trade, Industry and EnergySeoul National UniversitySeoul National University Bundang Hospital
KeywordsGrapheneElectrodeOxideMaterials scienceElectrochemistryAdsorptionElectrochemical gas sensorUrineLayer (electronics)Conjugated systemPolymerChemical engineeringNanotechnologyChemistryComposite materialOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

An electrochemical based system with multiple layers coated on a functionalized graphene oxide Au electrode was developed to measure glucose concentration in urine in a more stable way. Two types of gold printed circuit boards were fabricated and graphene oxide was immobilized on their surface by chemical adsorption. Multiple layers, composed of a couple of polymers, were uniformly coated on the surface electrode. This device exhibited higher electrochemical responses against glucose, a greater resistivity in the presence of interferential substances in urine, and durable stabilities for longer periods of time than conventional units. The efficiency in current level according to the order and ratio of solution was evaluated during the immobilization of the layer. The fabricated electrodes were then also evaluated using hyperglycemic clinical samples and compared with the patterns of blood glucose measured with commercially available glucose meters. Our findings show that not only was their pattern similar but this similarity is well correlated.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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