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Record W2042453278 · doi:10.1109/icecs.2007.4511015

Electro-Enzymatic Glucose Sensor Using Hybrid Polymer Fabrication Process

2007· article· en· W2042453278 on OpenAlexaff
Jasbir N. Patel, Bożena Kamińska, Bonnie L. Gray, Byron D. Gates

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPolydimethylsiloxaneFabricationPhotoresistMaterials scienceSubstrate (aquarium)ElectrodeLayer (electronics)NanotechnologyPolymerOptoelectronicsChemistryComposite material

Abstract

fetched live from OpenAlex

In this article, we present an electro-enzymatic glucose sensor fabricated using a novel self-aligned and hybrid polymer fabrication process. The self-aligned fabrication process was carried out using polydimethylsiloxane (PDMS) as a process substrate material, SU-8 (a negative, epoxy based photoresist) as a sensor substrate material and gold as an electrode material. The electro-enzymatic glucose sensor was assembled from microfabricated components using a self-registration step. The sensor substrate is optically transparent and flexible. Utilizing the process, a wide range of bio-sensors for different constituents (e.g. lactate, pO2etc.) can be fabricated. The glucose sensor was successfully fabricated using our new multilayer SU-8 process on PDMS substrate. The sensor thickness was measured between 117.15 μm and 140.15 μm. The current response of the multi-layer electroenzymatic sensor using different glucose concentrations is also measured. Besides, the current response for long term stability is also presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2007
Admission routes1
Has abstractyes

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