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Record W2010815734 · doi:10.1002/biot.200700236

Multiplex pathogen detection based on spatially addressable microarrays of barcoded resins

2008· article· en· W2010815734 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

VenueBiotechnology Journal · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsNational Institute for NanotechnologyUniversity of AlbertaSteacie Institute for Molecular Sciences
FundersNational Institute of Biomedical Imaging and Bioengineering
KeywordsMultiplexDNA microarrayComputational biologyNanotechnologyBiologyComputer scienceBioinformaticsMaterials scienceGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

Suspension microsphere immunoassays are rapidly gaining recognition in antigen identification and infectious disease biodetection due to their simplicity, versatility and high-throughput multiplex screening. We demonstrate a multiplex assay based on antibody-functionalized barcoded resins (BCRs) to identify pathogen antigens in complex biological fluids. The binding event of a particular antibody on given bead (fluorescence) and the identification of the specific pathogen agent (vibrational fingerprint of the bead) can be achieved in a dispersive Raman system by exciting the sample with two different laser lines. Anthrax protective antigen, Franciscella tularensis lipopolysaccharide and CD14 antigens were accurately identified and quantified in tetraplex assays with a detection limit of 1 ng/mL. The rapid, versatile and simple analysis enabled by the BCRs demonstrates their potential for multiplex antigen detection and identification in a reconfigurable microarray format.

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 score0.046
Threshold uncertainty score0.640

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 integrity0.0010.000
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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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