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Record W3028550487 · doi:10.1039/d0bm00574f

Nanobodies derived from Camelids represent versatile biomolecules for biomedical applications

2020· review· en· W3028550487 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

VenueBiomaterials Science · 2020
Typereview
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsInstitute of Cancer Research
FundersNational Laboratory of BiomacromoleculesNatural Science Research of Jiangsu Higher Education Institutions of ChinaPriority Academic Program Development of Jiangsu Higher Education InstitutionsNatural Science Foundation of Jiangsu ProvinceState Key Laboratory of Chemo/Biosensing and ChemometricsNanjing Medical UniversitySoutheast UniversityNational Natural Science Foundation of China
KeywordsBiomoleculeComputational biologyNanotechnologyComputer scienceChemistryBiologyMaterials science

Abstract

fetched live from OpenAlex

Nanobodies are antigen binding variable domains of heavy-chain antibodies without light-chains, and these biomolecules occur naturally in the serum of Camelidae species. Nanobodies have a compact structure and low molecular weight when compared with antibodies, and are the smallest active antigen-binding fragments. Because of their remarkable stability and manipulable characteristics, nanobodies have been incorporated into biomaterials and used as molecular recognition and tracing agents, drug delivery systems, molecular imaging tools and disease therapeutics. This review summarizes recent progress in this field focusing on nanobodies as versatile biomolecules for biomedical applications.

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 score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.096
GPT teacher head0.428
Teacher spread0.331 · 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