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Record W2068236518 · doi:10.5483/bmbrep.2005.38.4.399

Development of Array-based Technology for Detection of HAV Using Gold-DNA Probes

2005· article· en· W2068236518 on OpenAlexaff
Yefu Wang, Shawn S.‐C. Li, Lianlian Duan, Jianxin Zhai

Bibliographic record

VenueBMB Reports · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsWestern University
FundersZhongnan Hospital of Wuhan University
KeywordsAmpliconOligonucleotideHepatitis a virusNaked eyeColloidal goldHybridization probeMaterials scienceDNAVirologyBiologyNanotechnologyMolecular biologyPolymerase chain reactionDetection limitChemistryVirusGeneGeneticsNanoparticleChromatography

Abstract

fetched live from OpenAlex

A sensitive method for detection of Hepatitis A virus (HAV) by utilizing gold-DNA probe on an array was developed. Amino-modified oligodeoxynucleotides at the 5' position were arrayed on an activated glass surface to function as capture probes. Sandwich hybridization occurred among capture probes, the HAV amplicon, and gold nanoparticlesupported oligonucleotide probes. After a silver enhancement step, signals were detected by a standard flatbed scanner or just by naked eyes. As little as 100 fM of HAV amplicon could be detected on the array. Therefore, the array technology is an alternative to be applied in detection of HAV due to its low-cost and high-sensitivity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.285
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations18
Published2005
Admission routes1
Has abstractyes

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