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Record W2123917128 · doi:10.1039/c3an02068a

Dynamics of BSA adsorption onto a photoablated polymer surface in a dielectric microchip

2014· article· en· W2123917128 on OpenAlexaff
Mohammed Kechadi, Lila Chaal, Bernard Tribollet, Jean Gamby

Bibliographic record

VenueThe Analyst · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsBiosensorBiomoleculeDielectric spectroscopyMicroelectrodeAdsorptionDielectricPolymerMaterials scienceCoatingElectrodeNanotechnologySurface modificationAnalytical Chemistry (journal)ChemistryElectrochemistryOptoelectronicsChromatographyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Dielectric impedance spectroscopy in a microchip was used for monitoring the adsorption of biomolecules onto a heterogeneous polymer surface obtained after the photoablation process. The sensor comprises a thin dielectric layer with two parallel carbon microband electrodes on the one side, and the photoablated surface on the other. The biomolecules need not to be labelled, as in an optical biosensor, even if they need to be attached to the polymer surface coupled with the microelectrodes when a biomolecular interaction occurs. Based on this principle, a flow sensor has been developed to record the adsorption dynamics illustrated with BSA coating on the heterogeneous surface in a linear dynamic range from 1 picomolar to 1 nanomolar at a fixed low frequency. Modeling the dielectric interface using an appropriate equivalent circuit permits extraction of the values of the interfacial impedance for ultralow protein concentrations. The promising results obtained with this methodology make it a competing method in comparison with optical or electrochemical transduction for biosensor development.

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 score0.240
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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