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Record W2160062035 · doi:10.1039/c0cc05331g

Carbon-bonded silver nanoparticles: alkyne-functionalized ligands for SERS imaging of mammalian cells

2011· article· en· W2160062035 on OpenAlexaff
David C. Kennedy, Craig S. McKay, Li‐Lin Tay, Y Rouleau, John Paul Pezacki

Bibliographic record

VenueChemical Communications · 2011
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsInstitute for Microstructural SciencesUniversity of OttawaSteacie Institute for Molecular SciencesNational Research Council Canada
Fundersnot available
KeywordsAlkyneMoleculePlasmonNanotechnologyNanoparticleMaterials scienceSilver nanoparticleAqueous solutionCarbon fibersCombinatorial chemistryChemistryOrganic chemistryComposite number

Abstract

fetched live from OpenAlex

Silver nanoparticles bonded to terminal alkynes form stable particles in aqueous solution, produce strong SERS signals for molecular imaging that arise from the carbon-metal bond, and expand the scope of molecules that can be used to stably functionalize plasmonic particles for mammalian cell imaging applications. β-Lactams represent a class of biologically important molecules that can be adapted to SERS studies in this manner.

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)0.000
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 score0.010
Threshold uncertainty score0.442

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 science0.0010.000
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 head0.045
GPT teacher head0.258
Teacher spread0.213 · 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

Citations54
Published2011
Admission routes1
Has abstractyes

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