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Record W2050387685 · doi:10.1002/anie.200705982

Rolling Circle Amplification: Applications in Nanotechnology and Biodetection with Functional Nucleic Acids

2008· review· en· W2050387685 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

VenueAngewandte Chemie International Edition · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRolling circle replicationDeoxyribozymeMultiple displacement amplificationNanotechnologyDNAAptamerNucleic acidComputational biologyLoop-mediated isothermal amplificationPrimer (cosmetics)BiosensorDNA nanotechnologyGenomicsTemplateNanobiotechnologyDNA microarraygenomic DNABiologyMolecular biologyPolymerase chain reactionChemistryPolymeraseGenomeMaterials scienceGeneticsGeneDNA extraction

Abstract

fetched live from OpenAlex

Rolling circle amplification (RCA) is an isothermal, enzymatic process mediated by certain DNA polymerases in which long single-stranded (ss) DNA molecules are synthesized on a short circular ssDNA template by using a single DNA primer. A method traditionally used for ultrasensitive DNA detection in areas of genomics and diagnostics, RCA has been used more recently to generate large-scale DNA templates for the creation of periodic nanoassemblies. Various RCA strategies have also been developed for the production of repetitive sequences of DNA aptamers and DNAzymes as detection platforms for small molecules and proteins. In this way, RCA is rapidly becoming a highly versatile DNA amplification tool with wide-ranging applications in genomics, proteomics, diagnosis, biosensing, drug discovery, and nanotechnology.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score0.967

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 head0.018
GPT teacher head0.282
Teacher spread0.263 · 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