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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 OpenAlex

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.
fundA Canadian funder is recorded on the work.

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.

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)0.001
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 score0.069
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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