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Record W1984255770 · doi:10.1364/ol.32.003092

Enhanced surface plasmon resonance imaging detection of DNA hybridization on periodic gold nanoposts

2007· article· en· W1984255770 on OpenAlexafffund
Lidija Malic, Bo Cui, Teodor Veres, Maryam Tabrizian

Bibliographic record

VenueOptics Letters · 2007
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSurface plasmon resonanceMaterials scienceOpticsPlasmonScanning electron microscopeSurface plasmonElectron-beam lithographySIGNAL (programming language)BiosensorSubstrate (aquarium)Colloidal goldLocalized surface plasmonLithographyOptoelectronicsNanotechnologyResistPhysicsNanoparticle

Abstract

fetched live from OpenAlex

We explore periodic gold nanoposts as substrates for the enhanced surface plasmon resonance imaging (SPRi) detection of DNA hybridization. Rigorous coupled-wave analysis was used to model and design the nanopost-based SPRi biosensor. Arrayed gold nanoposts on gold-coated glass substrate, with various widths and periodicity, were fabricated using electron-beam lithography and characterized with scanning electron and atomic force microscopy. A scanning-angle SPRi apparatus was used to conduct the kinetic analysis of DNA hybridization on nanopost-based sensor surface and assess the corresponding SPR signal amplification. Experimental results showed that both the nanostructure size and period influenced the SPR signal enhancement; the optimized 30 nm height, 50 nm size, and 110 nm period nanoposts provided a fivefold SPR signal amplification compared with the plain 50 nm thick gold film used as control.

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 score0.057
Threshold uncertainty score0.805

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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

Citations83
Published2007
Admission routes2
Has abstractyes

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