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Record W4404695130 · doi:10.3390/bios14120569

All-Printed Microfluidic–Electrochemical Devices for Glucose Detection

2024· article· en· W4404695130 on OpenAlexafffund
Zexi Wang, Zhiyi Zhang, Chang‐Qing Xu

Bibliographic record

VenueBiosensors · 2024
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsNational Research Council CanadaMcMaster University
FundersNational Research Council Canada
KeywordsMicrofluidicsNanotechnologyElectrochemistryChemistryMaterials scienceBiomedical engineeringChromatographyMedicineElectrode

Abstract

fetched live from OpenAlex

Free-standing capillary microfluidic channels were directly printed over printed electrodes using a particle/polymer mixture to fabricate microfluidic-electrochemical devices on polyethylene terephthalate (PET) films. Printed devices with no electrode modification were demonstrated to have the lowest limit of detection (LOD) of 7 μM for sensing glucose. The study shows that both a low polymer concentration in the mixture for printing the microfluidic channels and surface modification of the printed microfluidic channels using 3-aminopropyltrimethoxysilane can substantially boost the device's performance. It also shows that both device structure and enzyme doping level of the devices play an important role in ensuring the best performance of the devices under various testing conditions.

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 score0.172
Threshold uncertainty score0.641

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 head0.012
GPT teacher head0.234
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

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

Citations2
Published2024
Admission routes2
Has abstractyes

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