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Record W2052089838 · doi:10.1364/ol.34.003598

Silicon photonic wire biosensor array for multiplexed real-time and label-free molecular detection

2009· article· en· W2052089838 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptics Letters · 2009
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsInstitute for Biological SciencesNational Research Council CanadaSteacie Institute for Molecular SciencesInstitute for Microstructural Sciences
Fundersnot available
KeywordsBiosensorAnalyteMaterials scienceInterferometryMicrofluidicsSensor arrayOpticsMultiplexingChipPhotonicsWaveguideOptical powerMach–Zehnder interferometerOptical fiberOptoelectronicsNanotechnologyChemistryComputer scienceTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

We demonstrate a silicon photonic wire waveguide biosensor array chip for the simultaneous monitoring of different molecular binding reactions. The chip is compatible with automated commercial spotting tools and contains a monolithically integrated microfluidic channel for sample delivery. Each array sensor element is a 1.8-mm-long spiral waveguide folded within a 130 microm diameter spot and is incorporated in a balanced Mach-Zehnder interferometer with a near temperature independent response. The sensors are arranged in a 400 microm spacing grid pattern and are addressed through cascaded 1x2 optical power splitters using light from a single input fiber. We demonstrate the real-time monitoring of antibody-antigen reactions using complementary and mismatched immunoglobulin G receptor-analyte pairs and bovine serum albumin. The measured level of detection for each sensor element corresponds to a surface coverage of less than 0.3 pg/mm(2).

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 score0.207
Threshold uncertainty score0.724

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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