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Record W2047535734 · doi:10.1021/ac203245j

In Situ Electrokinetic Enhancement for Self-Assembled-Monolayer-Based Electrochemical Biosensing

2012· article· en· W2047535734 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnalytical Chemistry · 2012
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthCanadian Association for the Study of the Liver
KeywordsElectrokinetic phenomenaChemistryElectrodeMonolayerElectrochemistryIn situNanotechnologyBiosensorSelf-assembled monolayerMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

This study reports a multifunctional electrode approach which directly implements electrokinetic enhancement on a self-assembled-monolayer-based electrochemical sensor for point-of-care diagnostics. Using urinary tract infections as a model system, we demonstrate that electrokinetic enhancement, which involves in situ stirring and heating, can enhance the sensitivity of the strain specific 16S rRNA hybridization assay for 1 order of magnitude and accelerate the time-limiting incubation step with a 6-fold reduction in the incubation time. Since the same electrode platform is used for both electrochemical signal enhancement and electrochemical sensing, the multifunctional electrode approach provides a highly effective strategy toward fully integrated lab-on-a-chip systems for various biomedical applications.

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.

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 score0.016
Threshold uncertainty score0.869

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 head0.231
Teacher spread0.223 · 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