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Record W4415614218 · doi:10.1021/acs.chemrev.5c00641

Chemical Tools to Characterize the Coordination Chemistry of Radionuclides for Radiopharmaceutical Applications

2025· review· en· W4415614218 on OpenAlexafffund
Eszter Boros, Peter Comba, Jonathan W. Engle, Charlene Harriswangler, Suzanne E. Lapi, Jason S. Lewis, Simona Mastroianni, Liviu M. Mirica, Carlos Platas‐Iglesias, Caterina F. Ramogida, Raphaël Tripier, Marianna Tosato

Bibliographic record

VenueChemical Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsSimon Fraser UniversityTRIUMF
FundersNational Cancer InstituteNational Institute on AgingXunta de GaliciaDivision of ChemistryCanada Research Coordinating CommitteeMinisterio de Ciencia, Innovación y Universidades
KeywordsContext (archaeology)InterfacingCoordination complexCharacterization (materials science)Transuranium elementPlutonium

Abstract

fetched live from OpenAlex

During the past decade, the advancement and approval of novel radiopharmaceuticals for clinical application has led to a resurgence of the field of radiochemistry and specifically the coordination chemistry of radionuclides. In addition to well established radionuclides, short-lived radioisotopes of other elements are becoming accessible using new isotope production methods, necessitating the development of coordination chemistry compatible with the aqueous chemistry of such elements under tracer level conditions. As radiochemistry with radioactive metal ions relevant for radiopharmaceuticals is conducted at the nano- to picomole scale, conventional chemical characterization techniques can generally not be applied. Therefore, careful consideration and interfacing of tracer-level compatible techniques and macroscopic characterization methods is required. This Review provides an in-depth survey of common, contemporary characterization strategies for the coordination chemistry of radionuclides, including case studies to demonstrate context and relevance for the prospective development of clinically translatable radiopharmaceuticals.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.161
GPT teacher head0.451
Teacher spread0.291 · 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

Citations9
Published2025
Admission routes2
Has abstractyes

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