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Record W4378965944 · doi:10.1109/jsen.2023.3279649

Concept of a Crossed Czerny–Turner Spectrometer With an Integrated Automatic Sampling System for Biodetection Using Ultrastable Gold Nanoparticles

2023· article· en· W4378965944 on OpenAlexaff
Shimwe Dominique Niyonambaza, Gabriel Lachance, Élodie Boisselier, Mounir Boukadoum, Amine Miled

Bibliographic record

VenueIEEE Sensors Journal · 2023
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversité du Québec à MontréalUniversité Laval
Fundersnot available
KeywordsSpectrometerColloidal goldNanoparticleMaterials scienceNanotechnologyPlasmonOptoelectronicsOpticsPhysics

Abstract

fetched live from OpenAlex

This work presents the design and implementation of a portable optofluidic system for biodetection based on ultrastable gold nanoparticles functionalized with a dopamine-binding aptamer. The automatic sampling and mixing fluidic system integrated into a spectrometer is configured to measure the gold nanoparticles’ plasmon band position. The novel molecule detection method based on ultrastable gold nanoparticles has been previously tested using dopamine as the target molecule. The optofluidic system designed for automatic bathochromic shift detection has an optical resolution of 1 nm using a 50-$\mu \text{m}$input slit. The proposed system, compared to other existing molecule detection techniques, has several advantages including portability and automatic detection for in situ 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.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.049
GPT teacher head0.287
Teacher spread0.238 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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