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Record W2783529529 · doi:10.14447/jnmes.v17i4.390

Determination of Lead (Pb2+) by Anodic Stripping Voltammetry Based on [Ru(NH3)6]3+/Nafion Modified Electrodes

2014· article· en· W2783529529 on OpenAlexvenueno aff
Shirley Palisoc, Michelle Natividad, Patricia Denise DeVera, Benjamin Simone B. Tuason

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2014
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNafionAnodic stripping voltammetryElectrodeInorganic chemistryAnodeCyclic voltammetryStripping (fiber)ElectrolyteMaterials scienceVoltammetrySupporting electrolyteIndium tin oxideAnalytical Chemistry (journal)ChemistryElectrochemistryChromatography

Abstract

fetched live from OpenAlex

Chemically modified [Ru(NH3)6]3+ doped Nafion® thin film was fabricated on indium tin oxide (ITO) coated glass electrodes by using the drop-coating method to detect heavy metal ions of Pb(II) in de-ionized water analyte solution via anodic stripping voltammetry (ASV). This study also determined the effect of varying the concentration of the mediator ([Ru(NH3)6]3+) on the detection of the said heavy metals. The redox mediator Ru(NH3)6]3+ used in the study was effectively incorporated and immobilized within the Nafion modified electrodes. Lead concentration in the electrolyte solution and the concentration of the redox mediator was varied to control the properties of the fabricated electrodes which utilized for heavy metal detection through ASV. The conducting properties of ITO electrodes were enhanced with the deposition of Nafion® attaining minimal interference. The stripping current peaks increased with the concentration of the heavy metal present in the solution as well as with the mediator concentration.

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)0.001
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 score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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