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Record W7051834544

Plasmonic nanopipette biosensor

2014· article· it· W7051834544 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

VenueMax Planck Digital Library · 2014
Typearticle
Languageit
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsPlasmonBiosensorNanoparticlePlasmonic nanoparticlesSurface-enhanced Raman spectroscopyNanoscopic scaleColloidal goldRaman spectroscopy
DOInot available

Abstract

fetched live from OpenAlex

Integrating a SERS immunoassay on a plasmonic "patch clamp" nanopipette enabled nanobiosensing for the detection of IgG. A SERS response was obtained using a sandwich assay benefiting from plasmon coupling between a capture Au nanoparticle (AuNP) on a nanotip and a second AuNP modified with a Raman active reporter and an antibody selective for IgG. The impact of nanoparticle shape and surface coverage was investigated alongside the choice of Raman active reporter, deposition pH, and plasmonic coupling, in an attempt to fully understand the plasmonic properties of nanopipettes and to optimize the nanobiosensor for the detection of IgG. These probes will find applications in various fields due to their nanoscale size leading to the possibility of spatially and temporally addressing their location near cells to monitor secretion of biomolecules.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.609
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.006

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 head0.003
GPT teacher head0.157
Teacher spread0.154 · 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