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Record W2937336022 · doi:10.3390/s19071686

Non-Enzymatic Impedimetric Sensor Based on 3-Aminophenylboronic Acid Functionalized Screen-Printed Carbon Electrode for Highly Sensitive Glucose Detection

2019· article· en· W2937336022 on OpenAlexafffund
Ricardo Adriano Dorledo de Faria, Hassan Iden, Luíz Guilherme Dias Heneine, Túlio Matencio, Younès Messaddeq

Bibliographic record

VenueSensors · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrodeBiosensorChemistryNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

A highly sensitive glucose sensor was prepared by a one-step method using 3-aminophenyl boronic acid as a unit of recognition and a screen-printed carbon electrode (SPCE) as an electrochemical transducer. Scanning Electron Microscopy confirmed the success of the functionalization of the SPCE due to the presence of clusters of boronic acid distributed on the carbon surface. In agreement with the Electrochemical Impedance Spectroscopy (EIS) tests performed before and after the functionalization, Cyclic Voltammetry results indicated that the electroactivity of the electrode decreased 37.9% owing to the presence of the poly phenylboronic acid on the electrode surface. EIS revealed that the sensor was capable to selectively detect glucose at a broad range of concentrations (limit of detection of 8.53 × 10−9 M), not recognizing fructose and sucrose. The device presented a stable impedimetric response when immediately prepared but suffered the influence of the storage time and some interfering species (dopamine, NaCl and animal serum). The response time at optimized conditions was estimated to be equal to 4.0 ± 0.6 s.

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 categoriesMeta-epidemiology (narrow)
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 score0.387
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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.

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

Citations32
Published2019
Admission routes2
Has abstractyes

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