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Record W4408700757 · doi:10.1117/12.3044026

Portable and multiplexed biosensors: advancing analytical chemiluminescence on pixelated detectors for point-of-need diagnostics

2025· article· en· W4408700757 on OpenAlexaff
Reza Abbasi, Sebastian Wachsmann‐Hogiu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsMcGill University
Fundersnot available
KeywordsChemiluminescenceMultiplexingDetectorBiosensorPoint (geometry)Computer scienceNanotechnologyMaterials scienceTelecommunicationsChemistryChromatography

Abstract

fetched live from OpenAlex

This research develops innovative biosensor platforms for efficient, portable, and cost-effective diagnostics at the point-of-need, integrating optical, microfluidic, and chemiluminescence technologies with CMOS image sensors. A novel CMOS image sensor-based biosensor is presented for rapid detection of microbial contamination, demonstrating high sensitivity and correlation with commercial methods. Additionally, a single-electrode electrochemiluminescence (SE-ECL) system on-CMOS is introduced for uric acid detection, showing high selectivity and reusability. A novel SE-ECL configuration for multiplexed detection of multiple analytes using color-coded luminophores is also presented, highlighting its value for complex analyses. These platforms have significant potential in medical diagnostics, environmental monitoring, and food safety.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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