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Record W3183851328 · doi:10.3390/ph14070701

Recent Advances in the Clinical Translation of Silicon Fluoride Acceptor (SiFA) 18F-Radiopharmaceuticals

2021· review· en· W3183851328 on OpenAlexaff
Lexi Gower-Fry, Travis Kronemann, Andreas Dorian, Yinglan Pu, Carolin Jaworski, Carmen Wängler, Peter Bartenstein, Leonie Beyer, Simon Lindner, Klaus Jurkschat, Björn Wängler, Justin J. Bailey, Ralf Schirrmacher

Bibliographic record

VenuePharmaceuticals · 2021
Typereview
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTranslation (biology)FluorideIn vivoAcceptorCombinatorial chemistryChemistryComputational biologyBiochemistryMessenger RNABiologyBiotechnology

Abstract

fetched live from OpenAlex

The incorporation of silicon fluoride acceptor (SiFA) moieties into a variety of molecules, such as peptides, proteins and biologically relevant small molecules, has improved the generation of 18F-radiopharmaceuticals for medical imaging. The efficient isotopic exchange radiofluorination process, in combination with the enhanced [18F]SiFA in vivo stability, make it a suitable strategy for fluorine-18 incorporation. This review will highlight the clinical applicability of [18F]SiFA-labeled compounds and discuss the significant radiotracers currently in clinical use.

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 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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.340
GPT teacher head0.583
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2021
Admission routes1
Has abstractyes

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