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Record W4220765103 · doi:10.1139/cjc-2021-0295

Graphite-based sensor amended with fumed silica for electrodetection of azithromycin

2022· article· en· W4220765103 on OpenAlexvenueno aff
Salma Mamdouh, M. Shehata, Amany M. Fekry, M.A. Ameer

Bibliographic record

VenueCanadian Journal of Chemistry · 2022
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsnot available
Fundersnot available
KeywordsFumed silicaChemistryDetection limitElectrodeDielectric spectroscopyScanning electron microscopeGraphiteAnalytical Chemistry (journal)Nuclear chemistryElectrochemistryChromatographyMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Azithromycin (AM) detection has become of great interest as being one of the prescribed medicines in the medication protocol in Egypt for the recent coronavirus disease 2019 pandemic. Herein, a carbon paste electrode was simply amended with fumed silica for determining AM. The characterization of the new material was done by different techniques, including scanning electron microscopy, transmission electron microscopy, and electrochemical impedance spectroscopy. The newly modified fumed silica carbon paste electrode exhibited a highly sensitive response toward the oxidation of 1.0 mmol/L AM in phosphate buffer solution (PBS) for a pH range of 5.0–10.0. The effect of varying AM concentrations was studied in PBS, pH 7.4, with a detection limit of 11 μmol/L and a quantification limit of 37 μmol/L. Eventually, the recently amended electrode attained reasonable sensitivity and constancy for AM detection in actual trials, such as blood plasma and pharmaceutical drugs.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.625

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)0.0010.000

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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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