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Record W2155697264 · doi:10.1016/j.aca.2014.04.055

Aptamer binding assays for proteins: The thrombin example—A review

2014· review· en· W2155697264 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnalytica Chimica Acta · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchU.S. Food and Drug AdministrationAlberta HealthCanada Research ChairsAlberta InnovatesAlberta Innovates - Health Solutions
KeywordsAptamerChemistryThrombinComputational biologyHomogeneousDNASystematic evolution of ligands by exponential enrichmentBiochemistryCombinatorial chemistryNanotechnologyBiophysicsRNAMolecular biologyBiologyPlatelet

Abstract

fetched live from OpenAlex

Experimentally selected single-stranded DNA and RNA aptamers are able to bind to specific target molecules with high affinity and specificity. Many analytical methods make use of affinity binding between the specific targets and their aptamers. In the development of these methods, thrombin is the most frequently used target molecule to demonstrate the proof-of-principle. This paper critically reviews more than one hundred assays that are based on aptamer binding to thrombin. This review focuses on homogeneous binding assays, electrochemical aptasensors, and affinity separation techniques. The emphasis of this review is placed on understanding the principles and unique features of the assays. The principles of most assays for thrombin are applicable to the determination of other molecular targets.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
GPT teacher head0.352
Teacher spread0.305 · 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