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Record W2797215270 · doi:10.5539/ijc.v10n2p16

Development and Optimization of a Glucose Biosensor Based on Tris [5-amino-1,10-Phenanthroline]Iron(II) Polymer Films

2018· article· en· W2797215270 on OpenAlexvenueno aff
Kenneth L. Brown, Kyle Cushman

Bibliographic record

VenueInternational Journal of Chemistry · 2018
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsnot available
Fundersnot available
KeywordsBiosensorGlucose oxidaseChemistryCyclic voltammetryGlutaraldehydeTrisDetection limitPolymerNuclear chemistryPhenanthrolineElectrodeRedoxPolymer chemistryInorganic chemistryChromatographyElectrochemistryOrganic chemistryBiochemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A bilayered glucose biosensor consisting of tris[5-amino-1, 10-phenanthroline]iron(II) polymer film redox mediator and a glucose oxidase layer was prepared on glassy carbon surfaces. The polymer film of the iron complex was immobilized onto the electrode using cyclic voltammetry via electropolymerization reactions, while the enzyme layer was formed using a BSA and glutaraldehyde crosslinking reaction. The biosensors gave the largest response in the pH range of 7-8 and were evaluated with respect to storage conditions of room temperature and 4oC. There was no significant difference between the detection of glucose using the biosensor stored at room temperature versus one stored at 4°C and both bilayered films remained active for 20 days. The detection limit of the biosensors was found to be 0.30 mM which corresponds to a signal to noise ratio of 3:1.

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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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