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Record W2046575673 · doi:10.1039/b821670c

Interaction of metal ions and DNA films on gold surfaces: an electrochemical impedance study

2009· article· en· W2046575673 on OpenAlexafffund
Xiaomin Bin, Heinz‐Bernhard Kraatz

Bibliographic record

VenueThe Analyst · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDielectric spectroscopyMetal ions in aqueous solutionMetalIonElectrochemistryAnalytical Chemistry (journal)ChemistryMaterials scienceInorganic chemistryElectrodePhysical chemistryChromatography

Abstract

fetched live from OpenAlex

Electrochemical impedance spectroscopy (EIS) has been used to investigate the effects of a number of metal ions with DNA films on gold surfaces exploiting [Fe(CN)6](3-/4-) as a solution-based redox probe. Alkaline earth metal ions Mg2+, Ca2+, trivalent Al3+, La3+ and divalent transition metal ions Ni2+, Cu2+, Cd2+ and Hg2+ have been selected in this study and the results are compared with previous studies on the effects of Zn2+ on the EIS of DNA films. All experimental results were evaluated with the help of equivalent circuits which allowed the extraction of resistive and capacitive components. For all metal ions studied here, addition of the metal ions causes a decrease in the charge transfer resistance. The difference of charge transfer resistance (DeltaR(ct)) of ds-DNA films in the presence and absence of the various metal ions is different and particular to any given metal ion. In addition, we studied the EIS of ds-DNA films containing a single A-C mismatch in the presence and absence of Ca2+, Zn2+, Cd2+ and Hg2+. DeltaR(ct) values for ds-DNA films with a single A-C mismatch is smaller than those of fully matched ds-DNA films.

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 score0.002
Threshold uncertainty score0.261

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 head0.011
GPT teacher head0.303
Teacher spread0.291 · 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

Citations38
Published2009
Admission routes2
Has abstractyes

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