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Record W4390487378 · doi:10.1002/jrs.6649

Three‐dimensional plasmonic substrate as surface‐enhanced Raman spectroscopy (SERS) tool for the detection of trace chemicals

2024· article· en· W4390487378 on OpenAlexafffund
Navneet Kaur, Gautam Das

Bibliographic record

VenueJournal of Raman Spectroscopy · 2024
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaMitacsCanada Foundation for Innovation
KeywordsRhodamine 6GRaman spectroscopyCrystal violetSurface-enhanced Raman spectroscopySubstrate (aquarium)PlasmonMaterials scienceNanorodFiberAdsorptionAnalytical Chemistry (journal)Raman scatteringChemistryOptoelectronicsNanotechnologyOpticsMoleculeChromatographyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A three‐dimensional (3D) plasmonic substrate was developed using gold nanorods (GNRs) onto a tapered fiber surface using optical tweezing. To determine the efficacy of the substrate, Raman spectra of two toxic chemicals Rhodamine 6G (R6G) and Crystal Violet (CV) were studied. The “dip and dry” method was used to adsorb the chemicals along the tapered fiber length. The minimum concentration detected for CV and R6G was 10 −12 M. We have reported the characteristics and unique features of the manufactured substrate.

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)0.001
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 score0.010
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.273
Teacher spread0.260 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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