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Record W4404593840 · doi:10.3390/molecules29235501

Use of Adsorption Properties of Resin for Water Sample Preparation in Voltammetric Determination of Se(IV) Using Bismuth Microelectrode

2024· article· en· W4404593840 on OpenAlexaboutno aff
Małgorzata Grabarczyk, Marzena Adamczyk, Cecylia Wardak

Bibliographic record

VenueMolecules · 2024
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMicroelectrodeBismuthAdsorptionSample (material)ChemistrySample preparationAnalytical Chemistry (journal)Inorganic chemistryChromatographyElectrodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

This paper proposes a simple, environmentally friendly, and efficient procedure for preparing natural water samples for the voltammetric determination of trace amounts of Se(IV). The method is based on premixing a sample with Amberlite XAD-7 resin at 50 °C. The composition of the 10 mL solution consists of the sample to be analysed, 0.1 mol L−1 of acetate buffer at pH = 4.0, and 0.5 g of Amberlite XAD-7. After 2 min of stirring, a voltammetric measurement is carried out using a fixed bismuth microelectrode using the following potentials: −2.5 V for 2 s and −0.55 V for 30 s. The voltammetry is recorded by varying the potential from −400 mV to −1000 mV. An undisturbed Se(IV) signal is obtained in the presence of 10 mg L−1 of Triton X-100, 5 mg L−1 of SDS, 10 mg L−1 of CTAB, 5 mg L−1 of Rhamnolipid, 5 mg L−1 of HA, 10 mg L−1 of FA, and 2 mg L−1 of NOM. The validity of the developed procedure is checked by analysing the certified reference materials SPS-SW1 (surface water) and TM-25.5 (Lake Ontario water) additionally enriched with surfactants and humic substances.

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 score0.062
Threshold uncertainty score0.266

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 head0.095
GPT teacher head0.311
Teacher spread0.216 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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