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Record W2025361273 · doi:10.1063/1.2826545

Enhancement of diffraction for biosensing applications via Bloch surface waves

2007· article· en· W2025361273 on OpenAlex
Marco Liscidini, J. E. Sipe

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

VenueApplied Physics Letters · 2007
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiffractionGratingDielectricBiosensorMaterials sciencePrismOpticsDiffraction gratingSurface plasmonNanophotonicsStack (abstract data type)OptoelectronicsSurface waveExcited stateDiffraction efficiencyPlasmonNanotechnologyPhysicsAtomic physics

Abstract

fetched live from OpenAlex

We propose a biosensor based on the diffraction of Bloch surface waves (BSWs) in periodic dielectric stacks. Significant enhancement of diffraction efficiency by a biomolecule grating placed on the multilayer is predicted when a BSW is excited through a prism in the Kretschmann configuration. Numerical calculations for BSW in a Si∕SiO2 dielectric stack show an increase of diffraction intensity up to three orders of magnitude with respect to the case of surface plasmon wave enhancement. The mechanism that leads to large field confinement and the absence of absorption losses in the dielectric system make this solution flexible and suitable to different grating periods.

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: none
Teacher disagreement score0.553
Threshold uncertainty score0.416

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 head0.008
GPT teacher head0.224
Teacher spread0.215 · 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