MétaCan
Menu
Back to cohort
Record W4386754369 · doi:10.1002/cbdv.202301008

Aptamers: Features, Synthesis and Applications

2023· review· en· W4386754369 on OpenAlex
Aiswarya P. U, Gopika Raj, Jinju John, Malavika Mohan K, Franklin John, Jinu George

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChemistry & Biodiversity · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsnot available
FundersDepartment of Science and Technology, Ministry of Science and Technology, IndiaNatural Sciences and Engineering Research Council of CanadaSacred Heart CollegeUniversity of Windsor
KeywordsAptamerNanotechnologyComputer scienceDrug deliveryComputational biologyBiochemical engineeringChemistryData scienceEngineeringBiologyMolecular biologyMaterials science

Abstract

fetched live from OpenAlex

Aptamers have become a topic of interest among the researchers and scientists since they not only possess all of the benefits of antibodies but also possess special qualities including heat stability, low cost, and limitless uses⋅ Here we give a review about the features, applications, and challenges of aptamers and also how they are beneficial over the antibodies for biomedical applications. Their unique features make aptamers a prominent tool in therapeutics, diagnostics, biosensors and targeted drug delivery. In conclusion, aptamers represent exciting materials for a variety of applications and can be modified to improve their properties and to extend their applications in biomedical field.

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 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 score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.027
GPT teacher head0.294
Teacher spread0.267 · 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