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Record W2157433810 · doi:10.1071/ch10091

PEGylated Gold Nanoparticles Functionalized with ß-Cyclodextrin Inclusion Complexes: Towards Metal Nanoparticle–Polymer–Carbohydrate Cluster Biohybrid Materials

2010· article· en· W2157433810 on OpenAlex
Jingquan Liu, Eko Setijadi, Yingkai Liu, Michael R. Whittaker, Cyrille Boyer, Thomas P. Davis

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

VenueAustralian Journal of Chemistry · 2010
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsChemistryNanoparticlePolyethylene glycolChain transferRaftDispersityColloidal goldPolymerReversible addition−fragmentation chain-transfer polymerizationCyclodextrinPolymer chemistrySurface plasmon resonancePolymerizationSurface modificationCombinatorial chemistryOrganic chemistryMaterials scienceNanotechnologyRadical polymerizationPhysical chemistry

Abstract

fetched live from OpenAlex

A cholesterol-functional trithiocarbonate reversible addition–fragmentation chain transfer (RAFT) agent was synthesized and employed to generate well-defined poly(polyethylene glycol) acrylate with cholesterol chain termini using RAFT polymerization. Subsequently, the polymers were grafted onto the surface of gold nanoparticles using the trithiocarbonate functionality to bind to the gold surface. The cholesterol moieties were then modified via complexation with ß-cyclodextrin. The step-by-step modification of gold nanoparticles was characterized by dynamic light scattering, attenuated total reflection infrared spectroscopy and surface plasmon resonance analysis.

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 categoriesInsufficient payload (model declined to judge)
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 score0.997

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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