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Record W3040652472 · doi:10.1364/oe.391012

Polarization-contrast surface plasmon imaging

2020· article· en· W3040652472 on OpenAlexafffund
Yevgeniy Mikhyeyev, Ribal Georges Sabat

Bibliographic record

VenueOptics Express · 2020
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsPolarizerMaterials scienceSurface plasmon resonanceRefractive indexPolarization (electrochemistry)Monochromatic colorSurface plasmonGratingRayLight intensityMicroscopyOrthogonal polarization spectral imagingPlasmonOptoelectronicsNanoparticlePhysicsLaserChemistryBirefringenceNanotechnology

Abstract

fetched live from OpenAlex

Silver-coated Crossed Surface Relief Gratings (CSRGs) are fabricated and used for imaging and detecting localized refractive index variations in inhomogeneous water-based solutions via polarization-contrast Surface Plasmon Resonance (SPR). When placed in between crossed polarizers, incident light was transmitted at intensity levels directly and precisely related to the local refractive index value. This occurred due to the in-plane polarization conversion of the SPR light in between the orthogonal grating vectors. When viewed with a camera, SPR light from a monochromatic source enabled the acquisition of polarization-contrast microscopy images of a water and silicon oil mixture placed over the CSRG's surface.

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)0.000
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 score0.075
Threshold uncertainty score0.446

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 head0.013
GPT teacher head0.232
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

Citations5
Published2020
Admission routes2
Has abstractyes

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