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Record W2051858267 · doi:10.1039/b509724j

Scanning Kelvin nanoprobe detection in materials science and biochemical analysis

2005· article· en· W2051858267 on OpenAlexafffund
Larisa‐Emilia Cheran, Saman Sadeghi, Michael Thompson

Bibliographic record

VenueThe Analyst · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanoprobeKelvin probe force microscopeBiomoleculeWork functionNanotechnologyAdsorptionSubstrate (aquarium)DesorptionMaterials scienceMoleculeChemistryAtomic force microscopyNanoparticlePhysical chemistry

Abstract

fetched live from OpenAlex

The Kelvin nanoprobe is an extremely sensitive instrument capable of discerning subtle molecular interactions using vibrating electromagnetic and acoustic fields. It is based on the measurement of a fundamental material property, the work function. Modulation of this substrate parameter is caused by the adsorption or desorption of molecules, oxidation, corrosion, contamination, mechanical stress, illumination, temperature changes, electrostatic charging, surface treatment, attached dipolar structures and/or the immobilization of biomolecules. The present article explains the general principles of the method and offers an indication of the wide range of possible applications, with an emphasis on potential use in the biotechnological arena.

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)0.001
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 score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.263
Teacher spread0.257 · 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

Citations28
Published2005
Admission routes2
Has abstractyes

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