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Record W4253002754 · doi:10.1021/bc300214z

Porphyrin–Lipid Stabilized Gold Nanoparticles for Surface Enhanced Raman Scattering Based Imaging

2012· article· en· W4253002754 on OpenAlexaff
Natalie C. M. Tam, Patrick Z. McVeigh, Thomas D. MacDonald, Arash Farhadi, Brian C. Wilson, Gang Zheng

Bibliographic record

VenueBioconjugate Chemistry · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsPorphyrinChemistryRaman scatteringRaman spectroscopyColloidal goldSurface-enhanced Raman spectroscopyFluorescenceNanoparticleMicroscopyConfocalMoleculeConfocal microscopyNanotechnologyPhotochemistryOrganic chemistryMaterials scienceOptics

Abstract

fetched live from OpenAlex

A porphyrin-phospholipid conjugate with quenched fluorescence was utilized to serve as both the Raman dye and a stabilizing, biocompatible surface coating agent on gold nanoparticles. Through simple synthesis and validation with spectroscopy and confocal microscopy, we show that this porphyrin-lipid stabilized AuNP is a novel SERS probe capable of cellular imaging. To date, this is the first use of porphyrin as a Raman reporter molecule for SERS based imaging.

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 score0.003

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)0.0010.000

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 head0.017
GPT teacher head0.247
Teacher spread0.229 · 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

Citations67
Published2012
Admission routes1
Has abstractyes

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