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Record W2087306120 · doi:10.1364/oe.15.012523

Phase-sensitive silicon-based total internal reflection sensor

2007· article· en· W2087306120 on OpenAlexafffund
Sergiy Patskovsky, Michel Meunier, Andrei V. Kabashin

Bibliographic record

VenueOptics Express · 2007
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRefractive indexTotal internal reflectionOpticsMaterials sciencePrismMicrofabricationSiliconReflection (computer programming)Phase (matter)X-ray opticsOptoelectronicsComputer sciencePhysicsFabrication

Abstract

fetched live from OpenAlex

A concept of phase-sensitive Si-based Total Internal Reflection bio- and chemical sensor is presented. The sensor uses the reflection of light from an internal edge of a Si prism, which is in contact with analyte material changing its index of refraction (thickness). Changes of the refractive index are monitored by measuring the differential phase shift between p- and s-polarized components of light reflected from the system. We show that due to a high refractive index of Si, such methodology leads to a high sensitivity and dynamic range of measurements. Furthermore, the Si-based platform offers an easy bioimmobilization step and excellent opportunities for the development of multi-channel microsensors taking advantage of the advanced state of development of Si-based microfabrication technologies.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.271
Teacher spread0.257 · 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

Citations28
Published2007
Admission routes2
Has abstractyes

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