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Record W3167573155 · doi:10.1038/s41598-021-99430-6

Diattenuation and retardance signature of plasmonic gold nanorods in turbid media revealed by Mueller matrix polarimetry

2021· article· en· W3167573155 on OpenAlexafffund
Subir K. Ray, Nirmalya Ghosh, I. Alex Vitkin

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldEngineering
TopicOptical Polarization and Ellipsometry
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMueller calculusNanorodPolarimetryMaterials sciencePolarization (electrochemistry)PlasmonOpticsScatteringNanotechnologyOptoelectronicsPhysicsChemistry

Abstract

fetched live from OpenAlex

Plasmonic gold nanorods (GNRs) are finding increasing use in biomedicine due to their unique electromagnetic properties, optical contrast enhancement and biocompatibility; they also show promise as polarization contrast agents. However, quantification of their polarization-enhancing properties within heterogeneous turbid media remains challenging. We report on polarization response in controlled tissue phantoms consisting of dielectric microsphere scatterers with varying admixtures of GRNs. Experimental Mueller matrix measurements and polarization sensitive Monte-Carlo simulations show excellent agreement. Despite the GNRs' 3D random orientation and distribution in the strong multiply scattering background, significant linear diattenuation and retardance were observed. These exclusive measurable characteristics of GNRs suggest their potential uses as contrast enhancers for polarimetric assessment of turbid biological tissue.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.005
GPT teacher head0.208
Teacher spread0.204 · 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

Citations8
Published2021
Admission routes2
Has abstractyes

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