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Record W1908452448 · doi:10.1139/cjc-2014-0024

Electrochemical studies of ascorbic acid, dopamine, and uric acid at a <scp>dl</scp>-norvaline-deposited glassy carbon electrode

2014· article· en· W1908452448 on OpenAlexvenueno aff
Mahmoud M. Kamel, Ehab M. Abdalla, Mohamed Ibrahim, Y. M. Temerk

Bibliographic record

VenueCanadian Journal of Chemistry · 2014
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryAscorbic acidGlassy carbonElectrochemistryDetection limitDifferential pulse voltammetryElectrodeNorvalineUric acidMalonateNuclear chemistryInorganic chemistryCyclic voltammetryChromatographyOrganic chemistryBiochemistryAmino acid

Abstract

fetched live from OpenAlex

The electrochemical behavior of ascorbic acid (AA), dopamine (DA), and uric acid (UA) on a dl-norvaline-modified glassy carbon electrode (GCE) was studied by cyclic voltammetry. The bare GCE failed to distinguish the oxidation peaks of AA, DA, and UA in phosphate-buffered solution (pH 5.0), while the dl-norvaline-modified GCE could separate them efficiently. In differential pulse voltammetric (DPV) measurements, the modified electrode resolved the overlapped voltammetric responses of AA, DA, and UA into three well-defined voltammetric peaks. Under optimum conditions, the anodic peak currents of DPV for AA, DA, and UA were proportional to the concentration in the range of 20–400, 1–40, and 15–180 μmol/L, respectively, with a correlation coefficient (r) of around 0.998. The detection limits were 5, 0.3, and 10 μmol/L (S/N = 3) for AA, DA, and UA, respectively. Satisfactory results were achieved for the determination of AA in vitamin C tablets, DA in a dopamine ampoule sample, and UA in human blood serum samples.

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)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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