MétaCan
Menu
Back to cohort
Record W2075349418 · doi:10.1021/la048328j

Gold Nanoparticle Embedded, Self-Sustained Chitosan Films as Substrates for Surface-Enhanced Raman Scattering

2004· article· en· W2075349418 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.

Bibliographic record

VenueLangmuir · 2004
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRaman scatteringChitosanMaterials scienceColloidal goldNanoparticleRaman spectroscopyNanotechnologyBiosensorTransmission electron microscopyNanocompositeSurface plasmon resonanceBiopolymerAbsorption (acoustics)Chemical engineeringNanostructureOpticsPolymerComposite material

Abstract

fetched live from OpenAlex

In this work, self-sustained, biocompatible, biodegradable films containing gold nanostructures have been fabricated for potential application in nanobioscience and ultrasensitive chemical and biochemical analysis. We report a novel synthesis of gold nanoparticles mediated by the biopolymer chitosan. Self-supporting thin films are formed from the resultant gold-chitosan nanocomposite solutions and characterized by UV-visible surface plasmon absorption, transmission electron microscopy, atomic force microscopy, infrared absorption, and Raman scattering measurements. Results demonstrate control over the size and distribution of the nanoparticles produced, which is promising for several applications, including the development of biosensors. As a proof of principle, we demonstrate that gold-chitosan films can be employed in trace analysis using surface-enhanced Raman scattering.

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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.561

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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