MétaCan
Menu
Back to cohort
Record W2006498831 · doi:10.1039/b314058j

Protein microarray scanning in label-free format by Kelvin nanoprobe

2004· article· en· W2006498831 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Analyst · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanoprobeChemistryAnalytical Chemistry (journal)Kelvin probe force microscopeSecondary ion mass spectrometryBiosensorMass spectrometryMicroscopyChromatographyNanotechnologyMaterials scienceNanoparticleBiochemistryAtomic force microscopy

Abstract

fetched live from OpenAlex

Surface-immobilized protein species deposited in the microarray format have been detected by time-of-flight secondary ion mass spectrometry and by scanning Kelvin nanoprobe. The former method was used to examine the nature of protein deposition on amine-coated glass slides and gold substrates in preparation for Kelvin measurements. Both gallium and SF(5)(+) ion sources were employed to produce positive and negative ion spectra of amino acids and polypeptides. Scanning Kelvin technology has been used to detect antibody-antigen interactions in a label-free protocol through measurement of the surface potential of the biochemical pair on indium tin oxide, amine-treated slides and gold substrates. The results show that good inter-spot reproducibility can be achieved and that deposited areas can be examined for homogeneity at 100 nm resolution. This work represents the first report on surface potential detection in protein microarray technology.

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 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 score0.036
Threshold uncertainty score0.279

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 science0.0000.000
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 head0.007
GPT teacher head0.250
Teacher spread0.243 · 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