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Record W2107564830 · doi:10.1002/adma.200601651

Protein Detecting Arrays Based on Cationic Polythiophene–DNA‐Aptamer Complexes

2006· article· en· W2107564830 on OpenAlexaff
M. Béra Abérem, Ahmed Najari, H.‐A. Ho, Jean-François Gravel, Philippe Nobert, Denis Boudreau, Mario Leclerc

Bibliographic record

VenueAdvanced Materials · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAptamerBiomoleculePolythiopheneMaterials scienceBiosensorCationic polymerizationNanotechnologyDNA microarrayDNAProteomicsCombinatorial chemistryMolecular biologyPolymerConductive polymerChemistryBiochemistryBiologyGene expressionPolymer chemistryGene

Abstract

fetched live from OpenAlex

By combining an appropriate DNA aptamer with a cationic polythiophene optical transducer, human thrombin can be specifically detected on microarrays in the attomole range in less than one hour without any tagging of the target. The system can be modified and utilized as a probe for the detection of various proteins or other biomolecules. This work opens new interesting possibilities for simple and rapid multiparametric analysis in genomics and proteomics.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
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

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

Citations113
Published2006
Admission routes1
Has abstractyes

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