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Record W2510495836 · doi:10.1139/cjc-2016-0129

Fabrication of a highly sensitive and selective electrochemical sensor based on chitosan-coated Fe<sub>3</sub>O<sub>4</sub> magnetic nanoparticle for determination of antibiotic ciprofloxacin and its application in biological samples

2016· article· en· W2510495836 on OpenAlexvenueno aff
Sara Dehdashtian, Mohammad Bagher Gholivand, Mojtaba Shamsipur, Azadeh Azadbakht, Ziba Karimi

Bibliographic record

VenueCanadian Journal of Chemistry · 2016
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsnot available
FundersRazi University
KeywordsDetection limitElectrochemical gas sensorChitosanDielectric spectroscopyDifferential pulse voltammetryChemistryElectrochemistryElectrodeCyclic voltammetryNanoparticleSelectivityNuclear chemistryScanning electron microscopeAnalytical Chemistry (journal)Carbon paste electrodeLinear rangeNanotechnologyMaterials scienceChromatographyOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A simple and sensitive sensor has been developed for the electrochemical determination of ciprofloxacin (CF). The proposed sensor was designed by chitosan-coated Fe 3 O 4 magnetic nanoparticle incorporated in the carbon paste electrode (CPE), which provides remarkably improved sensitivity for the electrochemical determination of CF. The proposed sensor was characterized with scanning electron microscopy and electrochemical impedance spectroscopy. Under optimum conditions, the sensor provides two linear differential pulse voltammetry responses in the range of 0.05–6 μmol/L and 6–75 μmol/L for CF with a detection limit of 0.01 μmol/L. The proposed sensor exhibited high sensitivity and good selectivity and was successfully applied for CF determination in serum and urine 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 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 score0.006
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)0.0000.000

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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

Citations20
Published2016
Admission routes1
Has abstractyes

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