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Record W2397778779 · doi:10.1007/978-1-62703-134-9_30

Multiplexed Surface Plasmon Resonance Imaging for Protein Biomarker Analysis

2012· article· en· W2397778779 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

VenueMethods in molecular biology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsALCAMSurface plasmon resonanceMicrofluidicsMolecular bindingNanotechnologyAnalyteProteomicsChemistryMolecular imagingBiomarkerMaterials scienceCellMoleculeBiologyNanoparticleBiochemistryChromatography

Abstract

fetched live from OpenAlex

The reliable detection of ligand and analyte binding is of significant importance for the field of medical diagnostics. Recent advances in proteomics and the rapid expansion in the number of identified protein biomarkers enhance the need for reliable techniques for their identification in complex samples. Surface plasmon resonance imaging (SPRi) provides label-free detection of this binding process in real-time. This chapter details the fabrication of an SPR imaging instrument and its use in analyzing molecular binding interactions with the use of a high-density microfluidic SPRi chip, capable of multiplexed analysis as well as various immobilization chemistries. Controlled recovery of bound biomarkers is demonstrated to enable their identification using mass spectrometry. Finally, activated leukocyte cell adhesion molecule (ALCAM), a protein biomarker associated with a variety of cancers, is identified from human crude cell lysates using the microfluidic surface plasmon resonance imaging (SPRi) instrument.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.167
Threshold uncertainty score0.755

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 science0.0000.000
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 head0.026
GPT teacher head0.413
Teacher spread0.388 · 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